研究者詳細 - 金　群

写真a

キン　グン

金　群

Scopus 論文情報

論文数: 432 Citation: 6172 h-index: 35

Click to view the Scopus page. The data was downloaded from Scopus API in August 25, 2025, via http://api.elsevier.com and http://www.scopus.com .

Google Scholar 情報（Citations per year）

Citation: 8590 h-index: 44 i10-index: 154

Click to view the Google Scholar page.

Scopus 情報

所属

人間科学学術院人間科学部

職名

教授

学位

博士（工学）

ホームページ

http://nislab.human.waseda.ac.jp/

プロフィール

Qun Jin is a professor in the Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Japan. He has been extensively engaged in research works in the fields of computer science, information systems, and human informatics, with a focus on understanding and supporting humans through convergent research. His recent research interests cover behavior and cognitive informatics, health informatics, big data, personal analytics and individual modeling, artificial intelligence and machine learning, LLM and generative AI, Ai agents, blockchain and privacy-preserving computing, metaverse, digital twin, IoT, trustworthy platforms for data federation, sharing, and utilization, cyber-physical-social systems, and applications in healthcare and learning support and for the realization of a carbon-neutral society. He is a foreign fellow of the Engineering Academy of Japan (EAJ).

経歴

2003年04月

-

継続中

早稲田大学人間科学学術院人間科学部人間情報科学科教授
2018年09月

-

2020年09月

早稲田大学人間科学学術院副学術院長（国際担当）
2018年09月

-

2020年09月

早稲田大学大学院人間科学研究科研究科長
2014年09月

-

2016年09月

早稲田大学人間科学学術院人間科学部人間情報科学科学科主任
1999年04月

-

2003年03月

会津大学コンピュータ理工学部助教授
1995年04月

-

1999年03月

徳島大学工学部知能情報工学科助教授
2020年06月

-

2025年06月

株式会社アイネス社外取締役

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所属学協会

　

　

　

ACM
　

　

　

IEEE Computer Society
　

　

　

IEEE
　

　

　

人工知能学会
　

　

　

情報処理学会
　

　

　

日本工学アカデミー
　

　

　

CCF

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研究分野

知能情報学人工知能・機械学習・生成AI・AIエージェント / データベースビッグデータ・パーソナルデータ分析 / ウェブ情報学、サービス情報学人間情報学 / 生命、健康、医療情報学スマートヘルス・個別化ヘルスケア / 学習支援システム個別化教育・学習支援 / 教育工学ｅラーニング支援 / 認知科学挙動認知情報学・個人モデル構築

研究キーワード

挙動・認知情報学
健康情報学
人工知能・機械学習
大規模言語モデルと生成AI
AIエージェント
ビッグデータ
パーソナルアナリティクスと個人モデル構築
デジタルツイン
サイバーセキュリティ
ブロックチェーン
メタバース
ヘルスケア・学習支援への適用
スマートエネルギーとカーボンニュートラルのための人間行動データ分析
ウェルビーイング・コンピューティング

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受賞

Andrew P. Sage Best Transactions Paper Award 2025 of IEEE Transactions on Computational Social Systems

2025年07月 IEEE SMC Hierarchical Federated Learning With Social Context Clustering-Based Participant Selection for Internet of Medical Things Applications

受賞者： X. Zhou, X. Ye, K.I. Wang, W. Liang, N.K.C. Nair, S. Shimizu, Z. Yan, Q. Jin
ACM Best Student Paper Award（IEA/AIE 2025）

2025年07月 ACM SIGAI To Earn Praise or to Avoid Denial: Classification of Approval Desires in SNS Posts Based on Sentiment Analysis with Generative AI

受賞者： E. Murata, Q. Jin
IEEE Best Student Paper Award（IEEE CyberSciTech 2024）

2024年11月 IEEE A Two-Stage Depression Recognition Model Based on Improved YOLOv5 and Spatial-Temporal CNN Transformer Network

受賞者： J. Zhao, Q. Jin
Best Paper Award 2024, CCF Transactions on Pervasive Computing and Interaction

2024年08月 China Computer Federation (CCF) and Springer Pre-braking behaviors analysis based on Hilbert–Huang transform

受賞者： B. Wu, Y. Zhu, R. Dong, K. Sato, S. Ikuno, S. Nishimura and Q. Jin
IEEE Transactions on Industrial Informatics Best Paper Award

2023年 Technical Committee on Industrail Informatics, IEEE Industrial Electronics Society Intelligent Small Object Detection Based on Digital Twinning for Smart Manufacturing in Industrial CPS

受賞者： X. Zhou, X. Xu, W. Liang, Z. Zeng, S. Shimizu, L.T. Yang, Q. Jin
IEEE Outstanding Leadership Award

2018年 IEEE Computational Intelligence Society and IEEE Computer Society General Chair of Fourth IEEE International Conference on Internet of People
IEEE Outstanding Leadership Award

2016年 IEEE Computer Society General Chair of First IEEE Cyber Science and Technology Congress
IEEE Outstanding Service Award

2013年 IEEE System, Man, and Cybernetics Society General Co-Chair of International Conference on Awareness Science and Technology and Ubi-Media Computing
Best Paper Award

2011年 Fourth IEEE International Conferences on Cyber, Physical and Social Computing
優秀賞（運用実践）

2005年教育システム情報学会・日本学術会議 ICTを利用した優秀教育実践コンテスト
Best Paper Award

2016年 Seventh International Conference on the Applications of Digital Information and Web Technologies
Best Paper Award

2014年 Sixth International Conference on Information Technology in Medicine and Education
Best Paper Award

2012年 Fifth IET International Conference on Ubi-Media Computing

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論文

MICCAI 2023 STS Challenge: A retrospective study of semi-supervised approaches for teeth segmentation.

Yaqi Wang 0002, Yifan Zhang, Xiaodiao Chen, Shuai Wang 0003, Dahong Qian, Fan Ye, Feng Xu, Hongyuan Zhang 0002, Ruilong Dan, Qianni Zhang, Xingru Huang, Zhao Huang, Jun Liu 0027, Zhiwen Zheng, Chengyu Wu, Yunxiang Li, Zhi Li, Zhean Ma, Weiwei Cui 0003, Shan Luo 0003, Chengkai Wang, Yifei Chen, Tianhao Li, Yi Liu, Xiang Feng, Jiaxue Ni, Dongyun Liu, Qixuan Wang, Zhouhao Lin, Wei Song, Yuanlin Li, Bing Wang, Chunshi Wang, Qiupu Chen, Mingqian Li, Huiyu Zhou 0001, Qun Jin

Pattern Recognit. 170 112049 - 112049 2026年 [査読有り]

担当区分：最終著者

DOI
Hilbert-Huang transform based pupil changes analysis for concentration assessment in skilled mowing.

Bo Wu, Yuan Wu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

Scientific reports 15 ( 1 ) 21862 - 21862 2025年07月 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

In the hilly and mountainous areas of Japan, mowing operations can only be carried out by human labor because of the steep slopes. However, the environment faced by workers when mowing is complex, requiring them to deal with different visual stimuli at the same time. These factors will also be reflected in the data of specific pupil changes, further impacting their concentration while mowing. Therefore, in this study, based on a set of experiments on various terrain (flat land and slope) in Hiroshima, Japan, an analysis method of human pupil changes was proposed based on action decomposition technology Hilbert-Huang Transform (HHT) which can be used to calculate the different frequency patterns (intrinsic mode function, IMF) that represent nonlinearity in pupil changes more effectively than Fourier Transform or Wavelet Transform. Based on the use of our proposed Multiple Comparisons and Filtering framework named MCFID, the IMFs which directly related to specific mowing actions (cutting and lifting) were found though the statistical tools. By monitoring the corresponding IMFs, it is possible to calculate the period of the corresponding pupil movement, and further inversely infer information such as the subject's concentration status. Our approach can also be validated using other pupil movement datasets. The results of the study can provide useful insights for training new lawn mowers, and the relevant data can be used as data accumulation for the development of future fall detection systems.

DOI PubMed
Intelligent games meeting with multi-agent deep reinforcement learning: a comprehensive review.

Yiqin Wang, Yufeng Wang 0001, Feng Tian, Jianhua Ma 0002, Qun Jin

Artificial Intelligence Review 58 ( 6 ) 165 - 165 2025年06月 [査読有り]

担当区分：最終著者

DOI
Decentralized Federated Graph Learning With Lightweight Zero Trust Architecture for Next-Generation Networking Security

Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Katsutoshi Yada, Laurence T. Yang, Jianhua Ma, Qun Jin

IEEE Journal on Selected Areas in Communications 43 ( 6 ) 1908 - 1922 2025年06月 [査読有り]

担当区分：最終著者

DOI
Locational False Data Injection Attack Detection in Smart Grid Using Recursive Variational Graph Autoencoder

Yufeng Wang, Ziyan Lu, Jianhua Ma, Qun Jin

IEEE Internet of Things Journal 12 ( 10 ) 13697 - 13708 2025年05月 [査読有り]

担当区分：最終著者

DOI

Scopus
Information Theoretic Learning-Enhanced Dual-Generative Adversarial Networks With Causal Representation for Robust OOD Generalization

Xiaokang Zhou, Xuzhe Zheng, Tian Shu, Wei Liang, Kevin I-Kai Wang, Lianyong Qi, Shohei Shimizu, Qun Jin

IEEE Transactions on Neural Networks and Learning Systems 36 ( 2 ) 2066 - 2079 2025年02月 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

Recently, machine/deep learning techniques are achieving remarkable success in a variety of intelligent control and management systems, promising to change the future of artificial intelligence (AI) scenarios. However, they still suffer from some intractable difficulty or limitations for model training, such as the out-of-distribution (OOD) issue, in modern smart manufacturing or intelligent transportation systems (ITSs). In this study, we newly design and introduce a deep generative model framework, which seamlessly incorporates the information theoretic learning (ITL) and causal representation learning (CRL) in a dual-generative adversarial network (Dual-GAN) architecture, aiming to enhance the robust OOD generalization in modern machine learning (ML) paradigms. In particular, an ITL- and CRL-enhanced Dual-GAN (ITCRL-DGAN) model is presented, which includes an autoencoder with CRL (AE-CRL) structure to aid the dual-adversarial training with causality-inspired feature representations and a Dual-GAN structure to improve the data augmentation in both feature and data levels. Following a newly designed feature separation strategy, a causal graph is built and improved based on the information theory, which can enhance the causally related factors among the separated core features and further enrich the feature representation with the counterfactual features via interventions based on the refined causal relationships. The ITL is incorporated to improve the extraction of low-dimensional feature representations and learn the optimized causal representations based on the idea of "information flow." A dual-adversarial training mechanism is then developed, which not only enables the generator to expand the boundary of feature distribution in accordance with the optimized feature representation from AE-CRL, but also allows the discriminator to further verify and improve the quality of the augmented data for OOD generalization. Experiment and evaluation results based on an open-source dataset demonstrate the outstanding learning efficiency and classification performance of our proposed model for robust OOD generalization in modern smart applications compared with three baseline methods.

DOI PubMed
STCA-LLM: Spatial-Temporal Cross-Attention Large Language Model for Wind Speed Forecasting

Chengjie Zhou, Yufeng Wang, Jianhua Ma, Qun Jin

IEEE Internet of Things Journal 2025年 [査読有り]

担当区分：最終著者

DOI
MFFTD: A Multiscale Feature Fusion Transformer Detector for Electricity Theft Based on Semi-Supervised Learning

Yufeng Wang, Zhijie Wu, Jianhua Ma, Qun Jin

IEEE Transactions on Instrumentation and Measurement 74 1 - 10 2025年 [査読有り]

担当区分：最終著者

DOI
Adaptive Weighting via Federated Evaluation Mechanism for Domain Adaptation with Edge Devices

Rui Zhao, Xiao Yang, Peng Zhi, Rui Zhou, Qingguo Zhou, Qun Jin

ACM Transactions on Sensor Networks 2024年07月 [査読有り]

担当区分：最終著者

DOI
Personalized Federated Learning with Model-Contrastive Learning for Multi-Modal User Modeling in Human-Centric Metaverse

Xiaokang Zhou, Qiuyue Yang, Xuzhe Zheng, Wei Liang, Kevin I.Kai Wang, Jianhua Ma, Yi Pan, Qun Jin

IEEE Journal on Selected Areas in Communications 42 ( 4 ) 817 - 831 2024年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

83

被引用数

(Scopus)
Group Behavior Prediction and Evolution in Social Networks

Jingchao Wang, Xinyi Zhang, Weimin Li, Xiao Yu, Fangfang Liu, Qun Jin

IEEE Intelligent Systems 39 ( 2 ) 62 - 65 2024年03月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Reconstructed Graph Neural Network With Knowledge Distillation for Lightweight Anomaly Detection

Xiaokang Zhou, Jiayi Wu, Wei Liang, Kevin I-Kai Wang, Zheng Yan, Laurence T. Yang, Qun Jin

IEEE Transactions on Neural Networks and Learning Systems 35 ( 9 ) 11817 - 11828 2024年 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

The proliferation of Internet-of-Things (IoT) technologies in modern smart society enables massive data exchange for offering intelligent services. It becomes essential to ensure secure communications while exchanging highly sensitive IoT data efficiently, which leads to high demands for lightweight models or algorithms with limited computation capability provided by individual IoT devices. In this study, a graph representation learning model, which seamlessly incorporates graph neural network (GNN) and knowledge distillation (KD) techniques, named reconstructed graph with global-local distillation (RG-GLD), is designed to realize the lightweight anomaly detection across IoT communication networks. In particular, a new graph network reconstruction strategy, which treats data communications as nodes in a directed graph while edges are then connected according to two specifically defined rules, is devised and applied to facilitate the graph representation learning in secure and efficient IoT communications. Both the structural and traffic features are then extracted from the graph data and flow data respectively, based on the graph attention network (GAT) and multilayer perceptron (MLP) techniques. These can benefit the GNN-based KD process in accordance with the more effective feature fusion and representation, considering both structural and data levels across the dynamic IoT networks. Furthermore, a lightweight local subgraph preservation mechanism improved by the graph attention mechanism and downsampling scheme to better utilize the topological information, and a so-called global information alignment defined based on the self-attention mechanism to effectively preserve the global information, are developed and incorporated in a refined graph attention based KD scheme. Compared with four different baseline methods, experiments and evaluations conducted based on two public datasets demonstrate the usefulness and effectiveness of our proposed model in improving the efficiency of knowledge transfer with higher classification accuracy but lower computational load, which can be deployed for lightweight anomaly detection in sustainable IoT computing environments.

DOI PubMed

Scopus

60

被引用数

(Scopus)
LASGRec: A Personalized Recommender Based on Learnable Attribute Sampling and Graph Neural Network

Yufeng Wang, Xun Huang, Jianhua Ma, Qun Jin

IEEE Transactions on Computational Social Systems 2024年 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
HGCR: A Heterogeneous Graph-Enhanced Interactive Course Recommendation Scheme for Online Learning

Yufeng Wang, Dehua Ma, Jianhua Ma, Qun Jin

IEEE Transactions on Learning Technologies 2024年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
TE-TFN: A Text-enhanced Transformer Fusion Network for Multimodal Knowledge Graph Completion

Jingchao Wang, Xiao Liu, Weimin Li, Fangfang Liu, Xing Wu, Qun Jin

IEEE Intelligent Systems 39 ( 3 ) 54 - 62 2024年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Guest Editorial: Special Issue on Responsible AI in Social Computing

Qinghua Lu, Weishan Zhang, Zhen Wang, Qun Jin, Vincenzo Piuri

IEEE Transactions on Computational Social Systems 2023年12月 [招待有り]

DOI

Scopus
Hierarchical Federated Learning With Social Context Clustering-Based Participant Selection for Internet of Medical Things Applications.

Xiaokang Zhou, Xiaozhou Ye, Kevin I-Kai Wang, Wei Liang 0006, Nirmal-Kumar C. Nair, Shohei Shimizu, Zheng Yan 0002, Qun Jin

IEEE Transactions on Computational Social Systems 10 ( 4 ) 1742 - 1751 2023年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

150

被引用数

(Scopus)
CDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound.

Ruilong Dan, Yunxiang Li, Yijie Wang, Xiaodiao Chen, Gangyong Jia, Shuai Wang 0003, Ruiquan Ge, Guiping Qian, Qun Jin, Juan Ye, Yaqi Wang

IEEE Journal of Biomedical and Health Informatics 27 ( 7 ) 3525 - 3536 2023年07月 [査読有り] [国際誌]

DOI PubMed

Scopus

7

被引用数

(Scopus)
Bi-Dueling DQN Enhanced Two-Stage Scheduling for Augmented Surveillance in Smart EMS.

Wei Liang 0006, Weiquan Xie, Xiaokang Zhou, Kevin I-Kai Wang, Jianhua Ma, Qun Jin

IEEE Transactions on Industrial Informatics 19 ( 7 ) 8218 - 8228 2023年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

16

被引用数

(Scopus)
Intelligent Containment Control With Double Constraints for Cloud-Based Collaborative Manufacturing.

Xiaokang Zhou, Hailiang Hou, Wei Liang 0006, Kevin I-Kai Wang, Qun Jin

IEEE Transactions on Industrial Informatics 19 ( 6 ) 7541 - 7551 2023年06月 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
Decentralized P2P Federated Learning for Privacy-Preserving and Resilient Mobile Robotic Systems.

Xiaokang Zhou, Wei Liang 0006, Kevin I-Kai Wang, Zheng Yan 0002, Laurence T. Yang, Wei Wei 0006, Jianhua Ma, Qun Jin

IEEE Wireless Communications 30 ( 2 ) 82 - 89 2023年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

102

被引用数

(Scopus)
Edge-Enabled Two-Stage Scheduling Based on Deep Reinforcement Learning for Internet of Everything.

Xiaokang Zhou, Wei Liang 0006, Ke Yan 0001, Weimin Li, Kevin I-Kai Wang, Jianhua Ma, Qun Jin

IEEE Internet of Things Journal 10 ( 4 ) 3295 - 3304 2023年02月 [査読有り]

担当区分：最終著者

DOI

Scopus

103

被引用数

(Scopus)
An Efficient Smart Contract Vulnerability Detector Based on Semantic Contract Graphs Using Approximate Graph Matching

Yingli Zhang, Jiali Ma, Xin Liu, Guodong Ye, Qun Jin, Jianhua Ma, Qingguo Zhou

IEEE Internet of Things Journal 2023年 [査読有り]

DOI

Scopus

10

被引用数

(Scopus)
Distribution Bias Aware Collaborative Generative Adversarial Network for Imbalanced Deep Learning in Industrial IoT.

Xiaokang Zhou, Yiyong Hu, Jiayi Wu, Wei Liang 0006, Jianhua Ma, Qun Jin

IEEE Transactions on Industrial Informatics 19 ( 1 ) 570 - 580 2023年 [査読有り]

担当区分：最終著者

DOI

Scopus

127

被引用数

(Scopus)
A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images

Zijing Jiang, Linyan Wang, Yaqi Wang, Gangyong Jia, Guodong Zeng, Jun Wang, Yunxiang Li, Dechao Chen, Guiping Qian, Qun Jin

IEEE/ACM Transactions on Computational Biology and Bioinformatics 21 ( 4 ) 701 - 714 2022年 [査読有り] [国際誌]

担当区分：最終著者

DOI PubMed

Scopus

5

被引用数

(Scopus)
PSARE: A RL-Based Online Participant Selection Scheme Incorporating Area Coverage Ratio and Degree in Mobile Crowdsensing.

Ying Xu, Yufeng Wang 0001, Jianhua Ma, Qun Jin

IEEE Transactions on Vehicular Technology 71 ( 10 ) 10923 - 10933 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

15

被引用数

(Scopus)
Earning While Learning: An Adversarial Multi-Armed Bandit Based Real-Time Bidding Scheme in Deregulated Electricity Market.

Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

IEEE Transactions on Network Science and Engineering 9 ( 6 ) 3991 - 4000 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.

Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qun Jin, Lingling Sun, Qianni Zhang, Qisi Lian, Guiping Qian, Neng Xia, Ruizi Peng, Kai Tang, Shuai Wang, Yaqi Wang

IEEE Journal of Biomedical and Health Informatics 26 ( 4 ) 1684 - 1695 2022年 [査読有り] [国際誌]

DOI PubMed

Scopus

29

被引用数

(Scopus)
Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems.

Xiaokang Zhou, Xuesong Xu, Wei Liang, Zhi Zeng, Shohei Shimizu, Laurence T. Yang, Qun Jin

IEEE Transactions on Industrial Informatics 18 ( 2 ) 1377 - 1386 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

236

被引用数

(Scopus)
Siamese Neural Network Based Few-Shot Learning for Anomaly Detection in Industrial Cyber-Physical Systems

Xiaokang Zhou, Wei Liang, Shohei Shimizu, Jianhua Ma, Qun Jin

IEEE Transactions on Industrial Informatics 17 ( 8 ) 5790 - 5798 2021年08月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

With the increasing population of Industry 4.0, both AI and smart techniques have been applied and become hotly discussed topics in industrial cyber-physical systems (CPS). Intelligent anomaly detection for identifying cyber-physical attacks to guarantee the work efficiency and safety is still a challenging issue, especially when dealing with few labeled data for cyber-physical security protection. In this article, we propose a few-shot learning model with Siamese convolutional neural network (FSL-SCNN), to alleviate the over-fitting issue and enhance the accuracy for intelligent anomaly detection in industrial CPS. A Siamese CNN encoding network is constructed to measure distances of input samples based on their optimized feature representations. A robust cost function design including three specific losses is then proposed to enhance the efficiency of training process. An intelligent anomaly detection algorithm is developed finally. Experiment results based on a fully labeled public dataset and a few labeled dataset demonstrate that our proposed FSL-SCNN can significantly improve false alarm rate (FAR) and F1 scores when detecting intrusion signals for industrial CPS security protection.

DOI
Variational LSTM Enhanced Anomaly Detection for Industrial Big Data

Xiaokang Zhou, Yiyong Hu, Wei Liang, Jianhua Ma, Qun Jin

IEEE Transactions on Industrial Informatics 17 ( 5 ) 3469 - 3477 2021年05月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

With the increasing population of Industry 4.0, industrial big data (IBD) has become a hotly discussed topic in digital and intelligent industry field. The security problem existing in the signal processing on large scale of data stream is still a challenge issue in industrial internet of things, especially when dealing with the high-dimensional anomaly detection for intelligent industrial application. In this article, to mitigate the inconsistency between dimensionality reduction and feature retention in imbalanced IBD, we propose a variational long short-term memory (VLSTM) learning model for intelligent anomaly detection based on reconstructed feature representation. An encoder-decoder neural network associated with a variational reparameterization scheme is designed to learn the low-dimensional feature representation from high-dimensional raw data. Three loss functions are defined and quantified to constrain the reconstructed hidden variable into a more explicit and meaningful form. A lightweight estimation network is then fed with the refined feature representation to identify anomalies in IBD. Experiments using a public IBD dataset named UNSW-NB15 demonstrate that the proposed VLSTM model can efficiently cope with imbalance and high-dimensional issues, and significantly improve the accuracy and reduce the false rate in anomaly detection for IBD according to F1, area under curve (AUC), and false alarm rate (FAR).

DOI
Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN

Yaqi Wang, Lingling Sun, Qun Jin

IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 ( 3 ) 951 - 962 2021年05月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this disease. Computer-aided diagnosis of pneumothorax on chest X-ray, as a prerequisite for a timely cure, has been widely studied, but it is still not satisfactory to achieve highly accurate results. In this paper, an image classification algorithm based on the deep convolutional neural network (DCNN) is proposed for high-resolution medical image analysis of pneumothorax X-rays, which features a Network In Network (NIN) for cleaning the data, random histogram equalization data augmentation processing, and a DCNN. The experimental results indicate that the proposed method can effectively increase the correct diagnosis rate of pneumothorax, and the Area under Curve (AUC) of the test verified in the experiment is 0.9844 on ZJU-2 test data and 0.9906 on the ChestX-ray14, respectively. In addition, a large number of atmospheric pleura samples are visualized and analyzed based on the experimental results and in-depth learning characteristics of the algorithm. The analysis results verify the validity of feature extraction for the network. Combined with the results of these two aspects, the proposed X-ray image processing algorithm can effectively improve the classification accuracy of pneumothorax photographs.

DOI PubMed
CCFS: A Confidence-Based Cost-Effective Feature Selection Scheme for Healthcare Data Classification

Yiyuan Chen, Yufeng Wang, Liang Cao, Qun Jin

IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 ( 3 ) 902 - 911 2021年05月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

Feature selection (FS) is one of the fundamental data processing techniques in various machine learning algorithms, especially for classification of healthcare data. However, it is a challenging issue due to the large search space. Binary Particle Swarm Optimization (BPSO) is an efficient evolutionary computation technique, and has been widely used in FS. In this paper, we proposed a Confidence-based and Cost-effective feature selection (CCFS) method using BPSO to improve the performance of healthcare data classification. Specifically, first, CCFS improves search effectiveness by developing a new updating mechanism that designs the feature confidence to explicitly take into account the fine-grained impact of each dimension in the particle on the classification performance. The feature confidence is composed of two measurements: the correlation between feature and categories, and historically selected frequency of each feature. Second, considering the fact that the acquisition costs of different features are naturally different, especially for medical data, and should be fully taken into account in practical applications, besides the classification performance, the feature cost and the feature reduction ratio are comprehensively incorporated into the design of fitness function. The proposed method has been verified in various UCI public datasets and compared with various benchmark schemes. The thoroughly experimental results show the effectiveness of the proposed method, in terms of accuracy and feature selection cost.

DOI PubMed
Guest Editorial: Special Issue on Hybrid Human-Artificial Intelligence for Social Computing.

Weishan Zhang, Huansheng Ning, Lu Liu 0001, Qun Jin, Vincenzo Piuri

IEEE Transactions on Computational Social Systems 8 ( 1 ) 118 - 121 2021年 [招待有り]

DOI

Scopus

10

被引用数

(Scopus)
Guest Editorial: Machine Learning for AI-Enhanced Healthcare and Medical Services: New Development and Promising Solution.

Ke Yan 0001, Zhiwei Ji, Qun Jin, Qing-Guo Wang

IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 ( 3 ) 850 - 851 2021年 [招待有り]

DOI

Scopus

10

被引用数

(Scopus)
Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-ray Images

Jingxiong Li, Yaqi Wang, Shuai Wang, Jun Wang, Jun Liu, Qun Jin, Lingling Sun

IEEE Journal of Biomedical and Health Informatics 25 ( 5 ) 1336 - 1346 2021年 [査読有り] [国際誌] [国際共著]

DOI PubMed
Research and Implementation of Chinese Couplet Generation System With Attention Based Transformer Mechanism

Yufeng Wang, Jiang Zhang, Bo Zhang, Qun Jin

IEEE Transactions on Computational Social Systems 9 ( 4 ) 1 - 9 2021年 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

Couplet is a unique art form in Chinese traditional culture. The development of deep neural network (DNN) technology makes it possible for computers to automatically generate couplets. Especially, Transformer is a DNN-based 'Encoder-Decoder' framework, and widely used in natural language processing (NLP). However, the existed Transformer mechanism cannot fully exploit the essential linguistic knowledge in Chinese, including the special format and requirements of Chinese couplets. Therefore, this article adapts the Transformer mechanism to generate meaningful Chinese couplets. Specifically, the contributions of our work are threefold. First, considering the fact that the words in the corresponding positions of the antecedent clause and the subsequent clause in a Chinese couplet always have same part-of-speech (pos, i.e., word class), pos information is intentionally added into the Transformer to improve the accuracy of the conceived couplet. Second, to deal with the large number of unregistered and low-frequency words in Chinese couplet, a specific unregistered/low-frequency word processing mechanism (UWP) is designed and combined with the Transformer model. Third, to further improve the coherence of couplets, we incorporate the polish mechanisms (PMs) into Transformer model. In terms of three evaluation criteria including bilingual evaluation understudy (BLEU), perplexity, and human evaluation, the experimental results demonstrate the effectiveness of our designed Chinese couplet generation system.

DOI
Intelligent Small Object Detection Based on Digital Twinning for Smart Manufacturing in Industrial CPS

Xiaokang Zhou, Xuesong Xu, Wei Liang, Zhi Zeng, Shohei Shimizu, Laurence T. Yang, Qun Jin

IEEE Transactions on Industrial Informatics 1 - 1 2021年 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

DOI
KFRNN: An Effective False Data Injection Attack Detection in Smart Grid Based on Kalman Filter and Recurrent Neural Network

Yufeng Wang, Zhihao Zhang, Jianhua Ma, Qun Jin

IEEE Internet of Things Journal 9 ( 9 ) 1 - 1 2021年 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

The smart grid is now increasingly dependent on smart devices to operate, which leaves space for cyber attacks. Especially, the intentionally designed false data injection attack (FDIA) can successfully bypass the traditional measurement residual-based bad data detection scheme. Considering that the smart grid data naturally contain linear and nonlinear components, inspired by parallel ensemble learning, especially by the stacking method, this article presents an effective two-level learner-based FDIA detection scheme using the Kalman filter and recurrent neural network (KFRNN). The first level includes two base learners, in which the Kalman filter is used for state prediction to fit linear data, and the recurrent neural network is used to fit the nonlinear data feature. The second-level learner uses the fully connected layer and backpropagation (BP) module to adaptively combine the results of two base learners. Then, through fitting Weibull distribution of the sum of square errors (SSEs) between the observed measurements and the predicted measurements, the dynamic threshold is obtained to judge whether FDIA occurs or not. Comprehensive simulation results show that our scheme has better performance than other neural network-based and ensemble learning-based FDIA detection schemes.

DOI
Academic Influence Aware and Multidimensional Network Analysis for Research Collaboration Navigation Based on Scholarly Big Data

Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Runhe Huang, Qun Jin

IEEE Transactions on Emerging Topics in Computing 9 ( 1 ) 246 - 257 2021年01月 [査読有り] [国際誌]

担当区分：最終著者, 責任著者

DOI
Guest Editorial: AI and Machine Learning Solution Cyber Intelligence Technologies: New Methodologies and Applications

Ke Yan, Lu Liu, Yong Xiang, Qun Jin

IEEE Transactions on Industrial Informatics 16 ( 10 ) 6626 - 6631 2020年10月 [招待有り] [国際誌] [国際共著]

担当区分：最終著者

DOI
An Intelligent Dynamic Offloading From Cloud to Edge for Smart IoT Systems With Big Data

Tian Wang, Yuzhu Liang, Yilin Zhang, Xi Zheng, Muhammad Arif, Jin Wang, Qun Jin

IEEE Transactions on Network Science and Engineering 7 ( 4 ) 2598 - 2607 2020年10月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者, 責任著者

　概要を見る

Intelligent networking and big data analytics are two important pillars for the operation of systems. Edge computing is frequently used in smart IoT systems, particularly in those which cannot be served efficiently through cloud computing due to the limitations in bandwidth, latency and Internet connectivity. However, applications always generate a large amount of data, which are pre-programmed and predefined to run on the cloud or edge platform and can't be changed at run time. The applications may gain better performance if they synergistically run on the cloud and edge platform. In this study, a novel algorithm called Dynamic Switching Algorithm is proposed to ensure intelligent dynamics where all tasks are either offloaded on cloud or edge according to the system's real-time conditions. We further divide applications into four types based on their real-time requirements. Each type of application is set to a reasonable latency to make sure the system to have less processing time. The results demonstrate that our method outperforms two state-of-the-art methods, decreasing both the average delay and energy consumption of offloading by 8.17%~66.90% and 3.76%~78.60% respectively. The experimental evaluations show that the performance of the proposed method could effectively offload tasks in smart IoT systems.

DOI
BciNet: A Biased Contest-Based Crowdsourcing Incentive Mechanism Through Exploiting Social Networks

Yufeng Wang, Wei Dai, Qun Jin, Jianhua Ma

IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 ( 8 ) 2926 - 2937 2020年08月 [査読有り] [国際誌] [国際共著]

　概要を見る

Crowdsourcing has proved to be a splendid tool to aggregate the knowledge from a pool of individuals in order to perform abundant microtasks efficiently. Recently, with the explosive growth of online social network, Word of Mouth (WoM)-based crowdsourcing systems have emerged, in which besides conducting the tasks by themselves, participants simultaneously recruit other individuals through exploiting their social networks to help solve crowdsourced tasks. This crowdsourcing paradigm can greatly facilitate to grow the pool of crowdworkers. However, there exist two conflicting challenges in designing an effective WoM-based incentive mechanism: 1) sybil attack and 2) heterogeneous effect of participants. That is, intuitively, incentivizing (usually compensating for) common-ability individuals will inevitably stimulate the behavior of sybil attack (i.e., some individuals create multiple sybils, and split the total efforts into those sybils to expect more compensation). This paper proposes a novel biased contest-based crowdsourcing incentive mechanism through exploiting social networks (BciNet), aiming to balance those two conflicting objectives. BciNet is composed of two phases. First, based on spreading activation model, an enhanced geometric virtual point dissemination mechanism is able to provide sybil-proof property and accommodate the realistic social network structure. Second, based on participants' virtual points, a biased contest gives more reward to less able participants. Through carefully calibrating the bias factor, simulation results based on the real dataset show that BciNet can greatly improve the amount of participants' effort levels, and actually be robust against the sybil attack. In brief, for a practical incentive mechanism, the methodology to address conflicting goals is to put rational individuals into dilemma: to be sybil or not to be, it is the problem, i.e., the potential gain from the sybils in the second phase may be offset by the loss in the first phase.

DOI
Deep-Learning-Enhanced Human Activity Recognition for Internet of Healthcare Things

Xiaokang Zhou, Wei Liang, Kevin I-Kai Wang, Hao Wang, Laurence T. Yang, Qun Jin

IEEE Internet of Things Journal 7 ( 7 ) 6429 - 6438 2020年07月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

Along with the advancement of several emerging computing paradigms and technologies, such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of Things (IoT) technologies have been applied in a variety of fields. In particular, the Internet of Healthcare Things (IoHT) is becoming increasingly important in human activity recognition (HAR) due to the rapid development of wearable and mobile devices. In this article, we focus on the deep-learning-enhanced HAR in IoHT environments. A semisupervised deep learning framework is designed and built for more accurate HAR, which efficiently uses and analyzes the weakly labeled sensor data to train the classifier learning model. To better solve the problem of the inadequately labeled sample, an intelligent autolabeling scheme based on deep Q-network (DQN) is developed with a newly designed distance-based reward rule which can improve the learning efficiency in IoT environments. A multisensor based data fusion mechanism is then developed to seamlessly integrate the on-body sensor data, context sensor data, and personal profile data together, and a long short-term memory (LSTM)-based classification method is proposed to identify fine-grained patterns according to the high-level features contextually extracted from the sequential motion data. Finally, experiments and evaluations are conducted to demonstrate the usefulness and effectiveness of the proposed method using real-world data.

DOI
BTR: A Feature-Based Bayesian Task Recommendation Scheme for Crowdsourcing System

Wei Dai, Yufeng Wang, Jianhua Ma, Qun Jin

IEEE Transactions on Computational Social Systems 7 ( 3 ) 780 - 789 2020年06月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

　概要を見る

The crowdsourcing system is a distributed problem-solving platform, in which tasks are delivered to the crowd (i.e., crowdworkers) in the form of an open call. Usually, large-scale crowdsourcing systems contain abundant microtasks, and the overhead of a crowdworker spending on searching the appropriate task may be comparable to the cost of completing the task. Therefore, task recommendation is necessary. However, existing work ignores the dynamics in crowdsourcing system, i.e., new tasks continually arrive, which leads to the issues of task cold-start. To overcome the challenge of the new coming task recommendation, this article proposes a feature-based Bayesian task recommendation (BTR) scheme. The key idea to deal with the dynamics of the crowdsourcing system lies in that the BTR learns the latent factor of the task through the task features instead of task ID and then learns the user's preference according to their historical behaviors. Specifically, based on task features and the user's historical behavior records, BTR can not only timely provide crowdworkers with personalized task recommendations but also solve the task cold-start problem. The simulations based on the real crowdsourced data set demonstrate that BTR performs better than other typical schemes that target at recommending the newly arrived tasks to crowdworkers.

DOI
Cyber-Enabled Well-Being Oriented Daily Living Support Based on Personal Data Analysis

Seiji Kasuya, Xiaokang Zhou, Kiichi Tago, Shoji Nishimura, Qun Jin

IEEE Transactions on Emerging Topics in Computing 8 ( 2 ) 493 - 502 2020年04月 [査読有り] [国際誌]

担当区分：最終著者, 責任著者

　概要を見る

We are living in a cyber-physical-social environment with a variety of lifestyles and values. Living support has become important in such a diverse society. Owing to the ability to collect a large amount of personal data or life logs in the cyber-physical-social environment, it is now possible for us to provide living support based on personal data analysis. Moreover, analyzing such data can facilitate a deep understanding of an individual. In this study, we focus on the provision of cyber-enabled well-being oriented daily living support for an individual based on personal data analysis. Three categories of personal data are identified from an individual's daily life data. In this paper, we discuss the basic concept, model, and framework for well-being oriented personal data analysis in order to offer suggestions and advices to improve the living quality of an individual. Finally, we report a feasibility study with an application scenario by using personal and environmental data.

DOI
DNN-DP: Differential privacy enabled deep neural network learning framework for sensitive crowdsourcing data

Y. Wang, M. Gu, J. Ma, Q. Jin

IEEE Transactions on Computational Social Systems 7 ( 1 ) 215 - 224 2020年02月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

DOI

Scopus

31

被引用数

(Scopus)
A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing

Tian Wang, Guangxue Zhang, Anfeng Liu, Md Zakirul Alam Bhuiyan, Qun Jin

IEEE Internet of Things Journal 6 ( 3 ) 4831 - 4843 2019年06月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者, 責任著者

　概要を見る

The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT's capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.

DOI
DP3: A Differential Privacy-based Privacy-Preserving Indoor Localization Mechanism

Y. Wang, M. Huang, Q. Jin, J. Ma

IEEE Communications Letters 22 ( 12 ) 2547 - 2550 2018年12月 [査読有り] [国際誌] [国際共著]

DOI

Scopus

38

被引用数

(Scopus)
Analysis of User Network and Correlation for Community Discovery Based on Topic-Aware Similarity and Behavioral Influence

Xiaokang Zhou, Bo Wu, Qun Jin

IEEE Transactions on Human-Machine Systems 48 ( 6 ) 559 - 571 2018年12月 [査読有り] [国際誌]

担当区分：最終著者, 責任著者

DOI
PPRank: Economically Selecting Initial Users for Influence Maximization in Social Networks

Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

IEEE SYSTEMS JOURNAL 11 ( 4 ) 2279 - 2290 2017年12月 [査読有り]

　概要を見る

This paper focuses on seeking a new heuristic scheme for an influence maximization problem in social networks: how to economically select a subset of individuals (so-called seeds) to trigger a large cascade of further adoptions of a new behavior based on a contagion process. Most existing works on selection of seeds assumed that the constant number k seeds could be selected, irrespective of the intrinsic property of each individual's different susceptibility of being influenced (e.g., it may be costly to persuade some seeds to adopt a new behavior). In this paper, a price-performance-ratio inspired heuristic scheme, PPRank, is proposed, which investigates how to economically select seeds within a given budget and meanwhile try to maximize the diffusion process. Our paper's contributions are threefold. First, we explicitly characterize each user with two distinct factors: the susceptibility of being influenced (SI) and influential power (IP) representing the ability to actively influence others and formulate users' SIs and IPs according to their social relations, and then, a convex price-demand curve-based model is utilized to properly convert each user's SI into persuasion cost (PC) representing the cost used to successfully make the individual adopt a new behavior. Furthermore, a novel cost-effective selection scheme is proposed, which adopts both the price performance ratio (PC-IP ratio) and user's IP as an integrated selection criterion and meanwhile explicitly takes into account the overlapping effect; finally, simulations using both artificially generated and real-trace network data illustrate that, under the same budgets, PPRank can achieve larger diffusion range than other heuristic and brute-force greedy schemes without taking users' persuasion costs into account.

DOI
Cybersecurity for Cyber-Enabled Multimedia Applications

Qun Jin, Yong Xiang, Guozi Sun, Yao Liu, Chin-Chen Chang

IEEE MULTIMEDIA 24 ( 4 ) 10 - 13 2017年10月 [招待有り]

担当区分：筆頭著者

DOI

Scopus

3

被引用数

(Scopus)
Analyzing Social Roles Based on a Hierarchical Model and Data Mining for Collective Decision-Making Support

Bo Wu, Xiaokang Zhou, Qun Jin, Fuhua Lin, Henry Leung

IEEE SYSTEMS JOURNAL 11 ( 1 ) 356 - 365 2017年03月 [査読有り]

担当区分：責任著者

DOI

Scopus

21

被引用数

(Scopus)
Enabling the Social Internet of Things and Social Cloud Introduction

Weishan Zhang, Qun Jin, Didier El Baz

IEEE CLOUD COMPUTING 2 ( 6 ) 6 - 9 2015年11月 [招待有り]

DOI

Scopus

9

被引用数

(Scopus)
Discovery of Action Patterns and User Correlations in Task-Oriented Processes for Goal-Driven Learning Recommendation

Xiaokang Zhou, Jian Chen, Bo Wu, Qun Jin

IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES 7 ( 3 ) 231 - 245 2014年07月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

42

被引用数

(Scopus)
LONET: An Interactive Search Network for Intelligent Lecture Path Generation

Neil Y. Yen, Timothy K. Shih, Qun Jin

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 4 ( 2 ) 1 - 27 2013年03月 [査読有り]

担当区分：最終著者

DOI

Scopus

17

被引用数

(Scopus)
Ranking Metrics and Search Guidance for Learning Object Repository

Neil Y. Yen, Timothy K. Shih, Louis R. Chao, Qun Jin

IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES 3 ( 3 ) 250 - 264 2010年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

59

被引用数

(Scopus)
Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI

Erina Murata, Qun Jin

IEA/AIE (1) 161 - 172 2026年 [査読有り]

担当区分：最終著者, 責任著者

DOI
Ego-centric multiple-correlation and temporal graph neural networks based residential load forecasting

Yufeng Wang, Tianxu Han, Lingxiao Rui, Jianhua Ma, Qun jin

Engineering Applications of Artificial Intelligence 2025年11月 [査読有り]

担当区分：最終著者

DOI
TF-MVGNN: an accurate traffic forecasting framework based on spatial-temporal graph neural network through exploiting multiple-view graph construction and learning.

Haoyuan Cheng, Yufeng Wang 0001, Jianhua Ma 0002, Qun Jin

Neural Comput. Appl. 37 ( 20 ) 14657 - 14671 2025年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Integrating Acupuncture and Herbal Medicine into Assisted Reproductive Technology: A Systematic Review and Meta-Analysis of East Asian Traditional Medicine

Xiangping Peng, Bo Wu, Siyu Zhou, Yinghan Xu, Atsushi Ogihara, Shoji Nishimura, Qun Jin, Gerhard Litscher

Healthcare 13 ( 11 ) 2025年06月 [査読有り] [国際誌]

　概要を見る

BACKGROUND: Assisted reproductive technologies (ARTs) are essential in treating infertility but often face limited success due to low implantation and live birth rates. East Asian traditional medicine (EATM), including acupuncture and herbal medicine (HM), may enhance physiological responses during ART cycles. This study evaluated the effectiveness and safety of EATM in improving clinical pregnancy and live birth outcomes in women undergoing ART. METHODS: This review, registered in PROSPERO (CRD42023411712), systematically searched 11 databases up to 31 March 2023. We included randomized controlled trials (RCTs) comparing EATM interventions to control groups. Data extraction and quality assessment were performed independently by two authors. Meta-analysis used the inverse-variance method in Stata 12.0. A total of 37 RCTs involving 10,776 women (aged 29-38) were analyzed. Studies addressed infertility causes including polycystic ovary syndrome, tubal blockage, diminished ovarian reserve, and unexplained infertility. Acupuncture therapies included body, electro-, laser, and auricular acupuncture. Herbal treatments were administered as powders, pills, granules, decoctions, and ointments based on traditional Chinese formulas. RESULTS: EATM interventions were associated with significant improvements in clinical pregnancy and live birth rates. Acupuncture increased clinical pregnancy rates (CPR: RR 1.316, 95% CI 1.171-1.480) and live birth rates (LBR: RR 1.287, 95% CI 1.081-1.533). HM also enhanced CPRs (RR 1.184) and LBRs (RR 1.147). Subgroup analysis showed true acupuncture and HM were more effective than sham or placebo. No significant differences in adverse events were found. CONCLUSIONS: EATM, particularly acupuncture and HM, appears to be a safe and effective complementary therapy that can be used to improve ART outcomes. Future research should focus on developing standardized acupuncture and herbal protocols to optimize integration with ART.

DOI PubMed
Financial risk assessment of imbalanced data based on nonlinear causal time-series network

Xiaoyang Li, Weimin Li, Xiao Yu, Zhongming Han, Qun Jin

Information Processing & Management 62 ( 3 ) 104025 - 104025 2025年05月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Improving Multimodal Sentiment Analysis with Unimodal Pseudo-label Generation

Jianing Zhao, Ou Deng, Qun Jin

Lecture Notes in Computer Science 165 - 179 2025年03月 [査読有り]

担当区分：最終著者, 責任著者

DOI
原発性卵巣機能不全患者に対する鍼治療を用いた体外受精成功の症例報告—Acupuncture-Assisted In Vitro Fertilization in a Patient with Primary Ovarian Insufficiency : A Case Study

彭湘萍, 徐桜晗, 金群, 西村昭治, 扇原淳

中医臨床 = Clinical journal of traditional Chinese medicine : 使える中医学の総合情報誌 46 ( 1 ) 114 - 119 2025年03月 [査読有り]
Research on predicting the sleep status of orthopedic pain patients based on machine learning

Yikang Yu, Yuxi Li, Saboor Saeed, Atsushi Ogihara, Shoji Nishimura, Chao Xu, Guiyuan Lv, Qun Jin

Clinical Traditional Medicine and Pharmacology 2025年03月 [査読有り]

担当区分：最終著者

DOI
Meta-Data-Guided Robust Deep Neural Network Classification with Noisy Label

Jie Lu, Yufeng Wang, Aiju Shi, Jianhua Ma, Qun Jin

Applied Sciences 2025年02月 [査読有り]

担当区分：最終著者

DOI
Analysis of combined impact of information and emotional content on user engagement based on social media data

Zhenzhen Xu, Ruichen Cong, Qun Jin

HCII 2025, Proceedings. Lecture Notes in Computer Science, Springer 2025 2025年 [査読有り]

担当区分：最終著者
Dynamic Dominate-Modal-aware Model for Multimodal Sentiment Analysis

Jianing Zhao, Qun Jin

HCII 2025, Proceedings. Lecture Notes in Computer Science, Springer 2025 2025年 [査読有り]

担当区分：最終著者
A systematic review and meta-analysis of deep learning and radiomics in predicting MGMT promoter methylation status in glioblastoma: Efficacy, reliability, and clinical implications.

Yu Chen, Yuehui Liao, Panfei Li, Wei Jin, Jingwan Fang, Junwei Huang, Yaning Feng, Changxiong Xie, Ruipeng Li, Qun Jin, Xiaobo Lai

Displays 89 103072 - 103072 2025年 [査読有り]

DOI
Exploratory and Interpretable Approach to Estimating Latent Health Risk Factors Without Using Domain Knowledge.

Ruichen Cong, Shoji Nishimura, Atsushi Ogihara, Qun Jin

Big Data Min. Anal. 8 ( 2 ) 447 - 457 2025年 [査読有り]

担当区分：最終著者, 責任著者

DOI
Exploring multi-granularity contextual semantics for fully inductive knowledge graph completion

Jingchao Wang, Weimin Li, Alex Munyole Luvembe, Xiao Yu, Xinyi Zhang, Fangyu Liu, Fangfang Liu, Hao Wang, Zhenhai Wang, Qun Jin

Expert Systems with Applications 260 125407 - 125407 2025年01月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Analyzing Lifestyle and Behavior with Causal Discovery in Health Data from Wearable Devices and Self-Assessments

Jing Zhang, Ruichen Cong, Ou Deng, Yuxi Li, Keishin Lam, Qun Jin

2024 IEEE International Conference on E-health Networking, Application &amp; Services (HealthCom) 1 - 6 2024年11月 [査読有り]

担当区分：最終著者

DOI
Species-specific model based on sequence and structural information for ubiquitination sites prediction.

Weimin Li, Nan Chen, Jie Wang, Yin Luo, Huazhong Liu, Jihong Ding, Qun Jin

Journal of molecular biology 436 ( 22 ) 168781 - 168781 2024年11月 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

Ubiquitination is a common post-translational modification of proteins in eukaryotic cells, and it is also a significant method of regulating protein biological function. Computational methods for predicting ubiquitination sites can serve as a cost-effective and time-saving alternative to experimental methods. Existing computational methods often build classifiers based on protein sequence information, physical and chemical properties of amino acids, evolutionary information, and structural parameters. However, structural information about most proteins cannot be found in existing databases directly. The features of proteins differ among species, and some species have small amounts of ubiquitinated proteins. Therefore, it is necessary to develop species-specific models that can be applied to datasets with small sample sizes. To solve these problems, we propose a species-specific model (SSUbi) based on a capsule network, which integrates proteins' sequence and structural information. In this model, the feature extraction module is composed of two sub-modules that extract multi-dimensional features from sequence and structural information respectively. In the submodule, the convolution operation is used to extract encoding dimension features, and the channel attention mechanism is used to extract feature map dimension features. After integrating the multi-dimensional features from both types of information, the species-specific capsule network further converts the features into capsule vectors and classifies species-specific ubiquitination sites. The experimental results show that SSUbi can effectively improve the prediction performance of species with small sample sizes and outperform other models.

DOI PubMed

Scopus

1

被引用数

(Scopus)
Multiple feature selection based on an optimization strategy for causal analysis of health data

Ruichen Cong, Ou Deng, Shoji Nishimura, Atsushi Ogihara, Qun Jin

Health Information Science and Systems 12 ( 1 ) 52 - 52 2024年11月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

1

被引用数

(Scopus)
Challenges and Emerging Issues for Generative AI and Hyper Intelligence

Jianhua Ma, Qun Jin, Hui-Huang Hsu, John Paul C. Vergara, Antonio Guerrieri, Claudio Miceli, Ao Guo

2024 IEEE Cyber Science and Technology Congress (CyberSciTech) 258 - 265 2024年11月 [査読有り]

DOI
Assessing ChatG PT -Generated Comments for Video Content Viewing in Online Learning

Jiaqi Wang, Jian Chen, Qun Jin

2024 IEEE Cyber Science and Technology Congress (CyberSciTech) 230 - 237 2024年11月 [査読有り]

担当区分：最終著者

DOI
A Two-Stage Depression Recognition Model Based on Improved YOLOv5 and Spatial-Temporal CNN-Transformer Network

Jianing ZHAO, Qun JIN

2024 IEEE Cyber Science and Technology Congress (CyberSciTech) 329 - 334 2024年11月 [査読有り]

担当区分：最終著者

DOI
Decoupling representation contrastive learning for carbon emission prediction and analysis based on time series

Xiao Liu, Qunpeng Hu, Jinsong Li, Weimin Li, Tong Liu, Mingjun Xin, Qun Jin

Applied Energy 2024年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
Blinding and blurring the multi-object tracker with adversarial perturbations

Haibo Pang, Rongqi Ma, Jie Su, Chengming Liu, Yufei Gao, Qun Jin

Neural Networks 176 106331 - 106331 2024年08月 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

Adversarial attack reveals a potential imperfection in deep models that they are susceptible to being tricked by imperceptible perturbations added to images. Recent deep multi-object trackers combine the functionalities of detection and association, rendering attacks on either the detector or the association component an effective means of deception. Existing attacks focus on increasing the frequency of ID switching, which greatly damages tracking stability, but is not enough to make the tracker completely ineffective. To fully explore the potential of adversarial attacks, we propose Blind-Blur Attack (BBA), a novel attack method based on spatio-temporal motion information to fool multi-object trackers. Specifically, a simple but efficient perturbation generator is trained with the blind-blur loss, simultaneously making the target invisible to the tracker and letting the background be regarded as moving targets. We take TraDeS as our main research tracker, and verify our attack method on other excellent algorithms (i.e., CenterTrack, FairMOT, and ByteTrack) on MOT-Challenge benchmark datasets (i.e., MOT16, MOT17, and MOT20). BBA attack reduced the MOTA of TraDeS and ByteTrack from 69.1 and 80.3 to -238.1 and -357.0, respectively, indicating that it is an efficient method with a high degrees of transferability.

DOI PubMed

Scopus

1

被引用数

(Scopus)
ConeE: Global and local context-enhanced embedding for inductive knowledge graph completion

Jingchao Wang, Weimin Li, Fangfang Liu, Zhenhai Wang, Alex Munyole Luvembe, Qun Jin, Quanke Pan, Fangyu Liu

Expert Systems with Applications 246 123116 - 123116 2024年07月 [査読有り]

DOI

Scopus

5

被引用数

(Scopus)
ECPAS: A Blockchain-based E-Commerce Price Auditing System

Toshiki Takakubo, Ruidong Li, Haihan Nan, Qun Jin, Zhou Su, Huaming Wu

ICC 2024 - IEEE International Conference on Communications 1334 - 1339 2024年06月 [査読有り]

DOI
Heterogeneous network influence maximization algorithm based on multi-scale propagation strength and repulsive force of propagation field

Chang Guo, Weimin Li, Jingchao Wang, Xiao Yu, Xiao Liu, Alex Munyole Luvembe, Can Wang, Qun Jin

Knowledge-Based Systems 291 2024年05月 [査読有り]

担当区分：最終著者

DOI

Scopus

15

被引用数

(Scopus)
LFAS: An electricity load forecasting framework assisted by cooperative multi-task learning-based spike occurrence prediction

Wei Shi, Yufeng Wang, Jianhua Ma, Qun Jin

2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) 212 - 217 2024年05月 [査読有り]

担当区分：最終著者

DOI
Spatial–Temporal Federated Transfer Learning with multi-sensor data fusion for cooperative positioning

Xiaokang Zhou, Qiuyue Yang, Qiang Liu, Wei Liang, Kevin Wang, Zhi Liu, Jianhua Ma, Qun Jin

Information Fusion 105 102182 - 102182 2024年05月 [査読有り]

担当区分：最終著者

DOI

Scopus

78

被引用数

(Scopus)
Preface of special issue on heterogeneous information network embedding and applications.

Weimin Li 0001, Lu Liu, Kevin I-Kai Wang, Qun Jin

Future Generation Computer Systems 152 331 - 332 2024年03月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Design of TAM-based framework for credibility and trend analysis in sharing economy: Behavioral intention and user experience on Airbnb as an instance.

Yenjou Wang, Jason C. Hung, Chun-Hong Huang, Sadiq Hussain, Neil Y. Yen, Qun Jin

Computer Science and Information Systems 21 ( 2 ) 547 - 568 2024年 [査読有り]

担当区分：最終著者

DOI
A locational false data injection attack detection method in smart grid based on adversarial variational autoencoders [Formula presented]

Yufeng Wang, Yangming Zhou, Jianhua Ma, Qun jin

Applied Soft Computing 151 111169 - 111169 2024年01月 [査読有り]

担当区分：最終著者

DOI

Scopus

9

被引用数

(Scopus)
Influence maximization algorithm based on group trust and local topology structure.

Chang Guo, Weimin Li, Fangfang Liu, Kexin Zhong, Xing Wu 0001, Yougang Zhao, Qun Jin

Neurocomputing 564 126936 - 126936 2024年01月 [査読有り]

担当区分：最終著者

DOI

Scopus

19

被引用数

(Scopus)
AffinityVAE: A multi-objective model for protein-ligand affinity prediction and drug design.

Mengying Wang, Weimin Li, Xiao Yu, Yin Luo, Ke Han, Can Wang, Qun Jin

Computational biology and chemistry 107 107971 - 107971 2023年12月 [査読有り] [国際誌]

担当区分：最終著者

　概要を見る

In the prediction of protein-ligand affinity, the traditional methods require a large amount of computing resources, and have certain limitations in predicting and simulating the structural changes. Although employing data-driven approaches can yield favorable outcomes in deep learning, it entails a lack of interpretability. Some methods may require additional structural information or domain knowledge to support the interpretation, which may limit their applicability. This paper proposes an affinity variational autoencoder (AffinityVAE) using interaction feature mapping and a variational autoencoder, which consists of a multi-objective model capable of end-to-end affinity prediction and drug discovery. In this study, the limitations of affinity prediction in terms of interpretability are tackled by proposing the concept of a protein-ligand interaction feature map. This increases the diversity and quantity of protein-ligand binding data by designing an adaptive autoencoder of target chemical properties to generate new ligands similar to known ligands and adding them to the original training set. AffinityVAE is then retrained using this extended training set to further validate the protein-ligand binding affinity prediction. Comparisons were conducted between the AffinityVAE and recent methods to demonstrate the high efficiency of the proposed model. The experimental results show that AffinityVAE has very high prediction performance, and it has the potential to enhance the diversity and the amount of protein-ligand binding data, which promotes the drug development.

DOI PubMed

Scopus

14

被引用数

(Scopus)
GOMPS: Global Attention-based Ophthalmic Image Measurement and Postoperative Appearance Prediction System.

Xingru Huang, Zhi Li, Lixia Lou, Ruilong Dan, Lingxiao Chen, Guodong Zeng, Gangyong Jia, Xiaodiao Chen, Qun Jin, Juan Ye, Yaqi Wang

Expert Syst. Appl. 232 120812 - 120812 2023年12月 [査読有り]

DOI

Scopus

5

被引用数

(Scopus)
Determining Important Features in Multidimensional Health Data for Individualized Precision Healthcare

Ruichen Cong, Jianlun Wu, Shoji Nishimura, Atsushi Ogihara, Qun Jin

2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) 0077 - 0083 2023年11月 [査読有り]

担当区分：最終著者

DOI
Dynamic Multi-view Group Preference Learning for group behavior prediction in social networks.

Weimin Li, Cai Zhang, Xiaokang Zhou, Qun Jin

Expert Syst. Appl. 231 120553 - 120553 2023年11月 [査読有り]

担当区分：最終著者

DOI

Scopus

11

被引用数

(Scopus)
Enabling inductive knowledge graph completion via structure-aware attention network.

Jingchao Wang, Weimin Li, Wei Liu, Can Wang 0004, Qun Jin

Applied Intelligence 53 ( 21 ) 25003 - 25027 2023年11月 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
Hic-KGQA: Improving multi-hop question answering over knowledge graph via hypergraph and inference chain.

Jingchao Wang, Weimin Li, Fangfang Liu, Bin Sheng, Wei Liu, Qun Jin

Knowl. Based Syst. 277 110810 - 110810 2023年10月 [査読有り]

担当区分：最終著者

DOI

Scopus

12

被引用数

(Scopus)
A short-term residential load forecasting scheme based on the multiple correlation-temporal graph neural networks.

Yufeng Wang 0001, Lingxiao Rui, Jianhua Ma, Qun Jin

Appl. Soft Comput. 146 110629 - 110629 2023年10月 [査読有り]

担当区分：最終著者

DOI

Scopus

25

被引用数

(Scopus)
SGNR: A Social Graph Neural Network Based Interactive Recommendation Scheme for E-Commerce

Dehua Ma, Yufeng Wang, Jianhua Ma, Qun Jin

Tsinghua Science and Technology 28 ( 4 ) 786 - 798 2023年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

40

被引用数

(Scopus)
A Trustworthy Decentralized System for Health Data Integration and Sharing: Design and Experimental Validation

Ruichen Cong, Yaping Ye, Jianlun Wu, Yuxi Li, Yuerong Chen, Yishan Bian, Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

Lecture Notes in Computer Science 125 - 134 2023年07月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

5

被引用数

(Scopus)
Rumor source localization in social networks based on infection potential energy.

Weimin Li, Chang Guo, Yanxia Liu, Xiaokang Zhou, Qun Jin, Mingjun Xin

Information Sciences 634 172 - 188 2023年07月 [査読有り]

DOI

Scopus

32

被引用数

(Scopus)
ADCB: Adaptive Dynamic Clustering of Bandits for Online Recommendation System.

Yufeng Wang 0001, Weidong Zhang, Jianhua Ma, Qun Jin

Neural Processing Letters 55 ( 2 ) 1155 - 1172 2023年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Guest Editorial: Special issue on machine learning and deep learning algorithms for complex networks.

Pasquale De Meo, Qun Jin, Jianguo Yao, Michael Sheng 0001

CAAI Trans. Intell. Technol. 8 ( 1 ) 1 - 2 2023年03月 [招待有り]

DOI

Scopus

2

被引用数

(Scopus)
Behavioral Analysis of Mowing Workers Based on Hilbert–Huang Transform: An Auxiliary Movement Analysis of Manual Mowing on the Slopes of Terraced Rice Fields

Bo Wu, Yuan Wu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

Agriculture (Switzerland) 13 ( 2 ) 2023年02月 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Message from the DIKW 2023 Chairs: HPCC/DSS/SmartCity/DependSys 2023

Qun Jin, Yucong Duan, Muhammad Usman Khan, Xiaolong Xu

Proceedings - 2023 IEEE International Conference on High Performance Computing and Communications, Data Science and Systems, Smart City and Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2023 xxxi 2023年 [招待有り]

担当区分：筆頭著者

DOI

Scopus
Causal Discovery of Health Features from Wearable Device and Traditional Chinese Medicine Diagnosis Data

Yuxi Li, Ou Deng, Atsushi Ogihara, Shoji Nishimura, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14055 LNCS 556 - 569 2023年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

2

被引用数

(Scopus)
FOSA: Full Information Maximum Likelihood (FIML) Optimized Self-Attention Imputation for Missing Data.

Ou Deng, Qun Jin

CoRR abs/2308.12388 2023年

担当区分：最終著者

DOI
Policy-Based Reinforcement Learning for Assortative Matching in Human Behavior Modeling.

Ou Deng, Qun Jin

HCI (19) 14029 LNCS 378 - 391 2023年 [査読有り]

担当区分：最終著者

DOI

Scopus
Investigating the Factors to Improve Discrimination of the Desire for Approval in Tweets by Incorporating Dependency Analysis.

Erina Murata, Kiichi Tago, Qun Jin

HCI (50) 316 - 325 2023年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Experimental Design and Validation of i-Comments for Online Learning Support.

Jiaqi Wang, Jian Chen, Qun Jin

HCI (30) 14040 LNCS 201 - 213 2023年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

1

被引用数

(Scopus)
Multidimensional Data Integration and Analysis for Youth Health Care During the Covid-19 Pandemic.

Jianlun Wu, Yaping Ye, Yuxi Li, Ruichen Cong, Yishan Bian, Yuerong Chen, Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

HCI (19) 14029 LNCS 154 - 168 2023年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

2

被引用数

(Scopus)
Coevolution modeling of group behavior and opinion based on public opinion perception.

Weimin Li, Chang Guo, Zhibin Deng, Fangfang Liu, Jianjia Wang, Ruiqiang Guo, Can Wang 0004, Qun Jin

Knowledge-Based Systems 270 110547 - 110547 2023年 [査読有り]

担当区分：最終著者

DOI

Scopus

22

被引用数

(Scopus)
Artificial intelligence of things (AIoT) data acquisition based on graph neural networks: A systematical review.

Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

Concurrency and Computation:Practice and Experience 35 ( 23 ) 2023年 [査読有り]

担当区分：最終著者

DOI

Scopus

16

被引用数

(Scopus)
LDP-Fed+: A robust and privacy-preserving federated learning based classification framework enabled by local differential privacy.

Yufeng Wang 0001, Xu Zhang, Jianhua Ma, Qun Jin

Concurrency and Computation:Practice and Experience 35 ( 19 ) 2023年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Multi-ledger Coordinating Mechanism by Smart Contract for Individual-Initiated Trustworthy Data Sharing.

Yenjou Wang, Ruichen Cong, Yixiao Liu, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

HCI (35) 232 - 243 2023年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Effectiveness, Policy, and User Acceptance of COVID-19 Contact-Tracing Apps in the Post–COVID-19 Pandemic Era: Experience and Comparative Study

Ming Xin Liu, Si Yu Zhou, Qun Jin, Shoji Nishimura, Atsushi Ogihara

JMIR Public Health and Surveillance 8 ( 10 ) e40233 2022年10月 [査読有り] [国際誌]

DOI PubMed

Scopus

8

被引用数

(Scopus)
i-Comments: On-screen Individualized Comments for Online Learning Support

Jiaqi Wang, Jian Chen, Qun Jin

2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) 1 - 5 2022年09月 [査読有り]

担当区分：最終著者

DOI
Design of a Vision Blind Spot Detection System Based on Depth Camera

Zijun Wang, Qun Jin, Bo Wu

2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) 1 - 5 2022年09月 [査読有り]

DOI
Preface

Qun Jin, Chin Chen Chang

ACM International Conference Proceeding Series V - VI 2022年07月 [招待有り]

担当区分：筆頭著者

DOI

Scopus
Analysis on the Subdivision of Skilled Mowing Movements on Slopes

Bo Wu, Yuan Wu, Shoji Nishimura, Qun Jin

Sensors 22 ( 4 ) 1372 - 1372 2022年02月 [査読有り] [国際誌]

担当区分：最終著者

DOI PubMed

Scopus

9

被引用数

(Scopus)
CAN: Effective cross features by global attention mechanism and neural network for ad click prediction

Wenjie Cai, Yufeng Wang, Jianhua Ma, Qun Jin

Tsinghua Science and Technology 27 ( 1 ) 186 - 195 2022年02月 [査読有り]

担当区分：最終著者

DOI

Scopus

21

被引用数

(Scopus)
Message from the General Chairs: ITME 2022

Xiaobo You, Qun Jin, Hong Liu, Xiansheng Liu

Proceedings - 2022 12th International Conference on Information Technology in Medicine and Education, ITME 2022 XXIII 2022年 [招待有り]

DOI

Scopus
Policy-Based Reinforcement Learning for Assortative Matching in Human Behavior Modeling.

Ou Deng, Qun Jin

CoRR abs/2211.03936 2022年

担当区分：最終著者

DOI
CDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound.

Ruilong Dan, Yunxiang Li, Yijie Wang, Gangyong Jia, Ruiquan Ge, Juan Ye, Qun Jin, Yaqi Wang

CoRR abs/2206.08524 2022年

　概要を見る

Precise and rapid categorization of images in the B-scan ultrasound modality
is vital for diagnosing ocular diseases. Nevertheless, distinguishing various
diseases in ultrasound still challenges experienced ophthalmologists. Thus a
novel contrastive disentangled network (CDNet) is developed in this work,
aiming to tackle the fine-grained image categorization (FGIC) challenges of
ocular abnormalities in ultrasound images, including intraocular tumor (IOT),
retinal detachment (RD), posterior scleral staphyloma (PSS), and vitreous
hemorrhage (VH). Three essential components of CDNet are the weakly-supervised
lesion localization module (WSLL), contrastive multi-zoom (CMZ) strategy, and
hyperspherical contrastive disentangled loss (HCD-Loss), respectively. These
components facilitate feature disentanglement for fine-grained recognition in
both the input and output aspects. The proposed CDNet is validated on our ZJU
Ocular Ultrasound Dataset (ZJUOUSD), consisting of 5213 samples. Furthermore,
the generalization ability of CDNet is validated on two public and widely-used
chest X-ray FGIC benchmarks. Quantitative and qualitative results demonstrate
the efficacy of our proposed CDNet, which achieves state-of-the-art performance
in the FGIC task. Code is available at:
https://github.com/ZeroOneGame/CDNet-for-OUS-FGIC .

DOI
An effective model-free Gaussian Process based online social media recommendation.

Jiawei Xu, Yufeng Wang 0001, Jianhua Ma, Qun Jin

2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)(iThings/GreenCom/CPSCom/SmartData/Cybermatics) 374 - 378 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
MARV: Multi-task learning and Attention based Rumor Verification scheme for Social Media.

Yufeng Wang 0001, Bo Zhang 0034, Jianhua Ma, Qun Jin

IEEE/CIC International Conference on Communications in China(ICCC) 94 - 98 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
An Extendable Sentiment Monitoring Model for SNS Considering Environmental Factors.

Yenjou Wang, Neil Y. Yen, Qun Jin

Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference 13315 LNCS 408 - 421 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Linguistic and Contextual Analysis of SNS Posts for Approval Desire.

Erina Murata, Kiichi Tago, Qun Jin

Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference 13315 LNCS 332 - 344 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

1

被引用数

(Scopus)
Analyzing Change on Emotion Scores of Tweets Before and After Machine Translation.

Karin Fukuda, Qun Jin

Social Computing and Social Media: Design, User Experience and Impact - 14th International Conference 13315 LNCS 294 - 308 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

2

被引用数

(Scopus)
Analysis on the Effect of Living Habits and Environment to Concentration.

Yukai Gu, Qun Jin

HCI International 2022 Posters - 24th International Conference on Human-Computer Interaction 1581 CCIS 129 - 136 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Improving Emotional Confusions in SNS Sentiment Analysis by Partial Redistribution of BERT Discrimination Results.

Yenjou Wang, Qun Jin

Big Data Analytics in Astronomy, Science, and Engineering - 10th International Conference on Big Data Analytics 13830 LNCS 199 - 210 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Measurement and verification of cognitive load in multimedia presentation using an eye tracker.

Ruichen Cong, Kiichi Tago, Qun Jin

Multimedia Tools and Applications 81 ( 19 ) 26821 - 26835 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

12

被引用数

(Scopus)
QAPP: A quality-aware and privacy-preserving medical image release scheme.

Xu Zhang, Yufeng Wang 0001, Jianhua Ma, Qun Jin

Information Fusion 88 281 - 295 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
SSPA: an effective semi-supervised peer assessment method for large scale MOOCs.

Yufeng Wang 0001, Hui Fang, Qun Jin, Jianhua Ma

Interactive Learning Environments 30 ( 1 ) 158 - 176 2022年 [査読有り]

DOI

Scopus

9

被引用数

(Scopus)
F-SWIR: Rumor Fick-spreading model considering fusion information decay in social networks.

Weimin Li, Dingmei Wei, Xiaokang Zhou, Shaohua Li, Qun Jin

Concurrency and Computation: Practice and Experience 34 ( 22 ) 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

11

被引用数

(Scopus)
Modeling social network behavior spread based on group cohesion under uncertain environment.

Weimin Li, Zhibin Deng, Xiaokang Zhou, Qun Jin, Bin Sheng

Concurrency and Computation: Practice and Experience 34 ( 21 ) 2022年 [査読有り]

DOI

Scopus

1

被引用数

(Scopus)
Secure Interoperation of Blockchain and IPFS Through Client Application Enabled by CP-ABE.

Ruichen Cong, Yixiao Liu, Yenjou Wang, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

HCI (32) 13333 LNCS 30 - 41 2022年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

3

被引用数

(Scopus)
Pre-braking behaviors analysis based on hilbert–huang transform

Bo Wu, Yishui Zhu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura, Qun Jin

CCF Transactions on Pervasive Computing and Interaction 5 ( 2 ) 157 - 182 2022年 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
Measurement and quantification of an individual's feelings for a place in personal data analysis

Seiji Kasuya, Kiichi Tago, Qun Jin

Human Behavior and Emerging Technologies 3 ( 5 ) 739 - 749 2021年12月 [査読有り]

担当区分：最終著者

DOI

Scopus
Analysis on Falling Risk of Elderly Workers when Mowing on a Slope via Motion Capture

Bo Wu, Yuan Wu, Shoji Nishimura, Qun Jin

2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) 890 - 895 2021年10月 [査読有り]

担当区分：最終著者

DOI
An Short-Term Residential Load Forecasting Scheme Using Multi-Task Learning

Yu Feng Wang, Can Bin Xiao, Yan Chen, Qun Jin

Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications 44 ( 3 ) 47 - 52 2021年06月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Individual-Initiated Auditable Access Control for Privacy-Preserved IoT Data Sharing with Blockchain

Ruichen Cong, Yixiao Liu, Kiichi Tago, Ruidong Li, Hitoshi Asaeda, Qun Jin

2021 IEEE International Conference on Communications Workshops (ICC Workshops) 1 - 6 2021年06月 [査読有り]

担当区分：最終著者

DOI
Evolutionary community discovery in dynamic social networks via resistance distance

Weimin Li, Heng Zhu, Shaohua Li, Hao Wang, Hongning Dai, Can Wang, Qun Jin

Expert Systems with Applications 171 114536 - 114536 2021年06月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者, 責任著者

　概要を見る

Traditional social community discovery methods concentrate mainly on static social networks, but the analysis of dynamic networks is a prerequisite for real-time and personalized social services. Through the study of community changes, the community structure in a dynamic network can be tracked over time, which helps in the mining of dynamic network information. In this paper, we propose a method of tracking dynamic community evolution that is based on resistance distance. Specifically, we model the time-varying features of dynamic networks using the convergence of a resistance-based distance. In our model, the heterogeneity of neighboring nodes can be obtained in the local topology of nodes by analyzing the resistance distance between nodes. We design a community discovery algorithm that essentially discovers community structures on dynamic networks by identifying the so-called core node. During the process of community evolution analysis, both the dynamic contribution of ordinary nodes and core nodes in each community are considered. In addition, to avoid the inclusion of spurious communities in the community structure, we define the notion of noise community and account for it in our algorithm. Experimental results show that the method proposed in this paper can yield better accuracy than other existing methods.

DOI

Scopus

27

被引用数

(Scopus)
Improving Diagnosis Estimation by Considering the Periodic Span of the Life Cycle Based on Personal Health Data

Kiichi Tago, Shoji Nishimura, Atsushi Ogihara, Qun Jin

Big Data Research 23 100176 - 100176 2021年02月 [査読有り] [国際誌]

担当区分：最終著者, 責任著者

　概要を見る

With the surge in popularity of wearable devices, collection of personal health data has become quite easy. Many studies have been conducted using health data to estimate the onset and progression of illness. However, life habits may vary among individuals. By analyzing the life cycle from health-related data, conventional studies may be improved. This study proposes a new approach to improving diagnosis estimation by considering the life cycle analyzed from health-related data. The periodic span of the life cycle is estimated via autocorrelation analysis. In the range of the periodic span, dimension reduction for health data is performed by principal component analysis, and health features are extracted and used for diagnosis estimation. In our experiment, we used personal health data and pulse diagnosis data collected by a traditional Chinese medicine doctor. Using six multi-label classification methods, we verified that a combination of pulse and health features could improve the accuracy of diagnosis estimation compared with that using only pulse features.

DOI

Scopus

5

被引用数

(Scopus)
Analysis of the Conversations on Twitter regarding HPV Vaccine

Daisuke Suzuki, Shoji Nishimura, Qun Jin, Atsushi Ogihara

Journal of Consumer Health on the Internet 25 ( 4 ) 397 - 406 2021年 [査読有り]

DOI

Scopus

3

被引用数

(Scopus)
Dispensed Transformer Network for Unsupervised Domain Adaptation.

Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou 0001, Qun Jin, Li Wang, Yaqi Wang

CoRR abs/2110.14944 2021年

　概要を見る

Accurate segmentation is a crucial step in medical image analysis and
applying supervised machine learning to segment the organs or lesions has been
substantiated effective. However, it is costly to perform data annotation that
provides ground truth labels for training the supervised algorithms, and the
high variance of data that comes from different domains tends to severely
degrade system performance over cross-site or cross-modality datasets. To
mitigate this problem, a novel unsupervised domain adaptation (UDA) method
named dispensed Transformer network (DTNet) is introduced in this paper. Our
novel DTNet contains three modules. First, a dispensed residual transformer
block is designed, which realizes global attention by dispensed interleaving
operation and deals with the excessive computational cost and GPU memory usage
of the Transformer. Second, a multi-scale consistency regularization is
proposed to alleviate the loss of details in the low-resolution output for
better feature alignment. Finally, a feature ranking discriminator is
introduced to automatically assign different weights to domain-gap features to
lessen the feature distribution distance, reducing the performance shift of two
domains. The proposed method is evaluated on large fluorescein angiography (FA)
retinal nonperfusion (RNP) cross-site dataset with 676 images and a wide used
cross-modality dataset from the MM-WHS challenge. Extensive results demonstrate
that our proposed network achieves the best performance in comparison with
several state-of-the-art techniques.
GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation.

Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

CoRR abs/2109.14813 2021年
Anatomy-Guided Parallel Bottleneck Transformer Network for Automated Evaluation of Root Canal Therapy.

Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qianni Zhang, Qun Jin, Lingling Sun, Qisi Lian, Neng Xia, Ruizi Peng, Kai Tang, Yaqi Wang, Shuai Wang

CoRR abs/2105.00381 2021年
An Extended Epidemic Model on Interconnected Networks for COVID-19 to Explore the Epidemic Dynamics.

Ou Deng, Kiichi Tago, Qun Jin

CoRR abs/2104.04695 2021年

担当区分：最終著者

　概要を見る

COVID-19 has resulted in a public health global crisis. The pandemic control
necessitates epidemic models that capture the trends and impacts on infectious
individuals. Many exciting models can implement this but they lack practical
interpretability. This study combines the epidemiological and network theories
and proposes a framework with causal interpretability in response to this
issue. This framework consists of an extended epidemic model in interconnected
networks and a dynamic structure that has major human mobility. The networked
causal analysis focuses on the stochastic processing mechanism. It highlights
the social infectivity as the intervention estimator between the observable
effect (the number of daily new cases) and unobservable causes (the number of
infectious persons). According to an experiment on the dataset for Tokyo
metropolitan areas, the computational results indicate the propagation features
of the symptomatic and asymptomatic infectious persons. These new
spatiotemporal findings can be beneficial for policy decision making.
DAST: An aggregation scheme for crowdsensed indoor data exploiting sequential long-tail features.

Yawen Zhong, Yichen Guo, Yufeng Wang 0001, Qun Jin

IEEE Wireless Communications and Networking Conference Workshops 1 - 6 2021年 [査読有り]

担当区分：最終著者

DOI

Scopus
GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation.

Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

Machine Learning in Medical Imaging - 12th International Workshop(MLMI@MICCAI) 12966 LNCS 386 - 395 2021年 [査読有り]

DOI

Scopus

60

被引用数

(Scopus)
VFAT: A Personalized HAR Scheme Through Exploiting Virtual Feature Adaptation Based on Transfer Learning.

Xiao Li 0014, Yufeng Wang 0001, Jianhua Ma, Qun Jin

19th IEEE International Conference on Embedded and Ubiquitous Computing(EUC) 1 - 8 2021年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
A Front-End Framework Selection Assistance System with Customizable Quantification Indicators Based on Analysis of Repository and Community Data.

Koichi Kiyokawa, Qun Jin

Big-Data-Analytics in Astronomy, Science, and Engineering - 9th International Conference on Big Data Analytics 13167 LNCS 41 - 55 2021年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
A Position and Area Localization Algorithm for Obstacles in the Environment of Sparsely-Deployed Sensors.

Zhigang Gao, Xiaowei Yang, Bo Wu 0007, Huijuan Lu, Jianhui Zhang, Wenjie Diao, Qun Jin

IEEE Access 9 39884 - 39896 2021年 [査読有り]

担当区分：最終著者

DOI

Scopus
Analyzing eye-movements of drivers with different experiences when making a turn

Bo Wu, Shoji Nishimura, Qun Jin, Yishui Zhu

Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020 502 - 507 2020年12月 [査読有り]

DOI

Scopus

4

被引用数

(Scopus)
The effect of eye movements and cultural factors on product color selection

Bo Wu, Yishui Zhu, Keping Yu, Shoji Nishimura, Qun Jin

Human-centric Computing and Information Sciences 10 ( 1 ) 2020年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

18

被引用数

(Scopus)
RV-ML: An Effective Rumor Verification Scheme Based on Multi-Task Learning Model

Qian Lv, Yufeng Wang, Bo Zhang, Qun Jin

IEEE Communications Letters 24 ( 11 ) 2527 - 2531 2020年11月 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
Analyzing Pre-braking Behaviors of Drivers with Varying Experience

Bo Wu, Shoji Nishimura, Qun Jin, Yishui Zhu

Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020 284 - 289 2020年08月 [査読有り]

DOI

Scopus

2

被引用数

(Scopus)
Personalized real-time movie recommendation system: Practical prototype and evaluation

Jiang Zhang, Yufeng Wang, Zhiyuan Yuan, Qun Jin

Tsinghua Science and Technology 25 ( 2 ) 180 - 191 2020年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

78

被引用数

(Scopus)
Three-hop velocity attenuation propagation model for influence maximization in social networks

Weimin Li, Yuting Fan, Jun Mo, Wei Liu, Can Wang, Minjun Xin, Qun Jin

World Wide Web 23 ( 2 ) 1261 - 1273 2020年03月 [査読有り]

担当区分：最終著者

DOI

Scopus

21

被引用数

(Scopus)
Improved Cascade R-CNN for Medical Images of Pulmonary Nodules Detection Combining Dilated HRNet

Shihuai Xu, Huijuan Lu, Minchao Ye, Ke Yan, Wenjie Zhu, Qun Jin

ACM International Conference Proceeding Series 283 - 288 2020年02月 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
Modified Hybrid Task Cascade for Lung Nodules Segmentation in CT Images with Guided Anchoring

Shihuai Xu, Huijuan Lu, Minchao Ye, Ke Yan, Wenjie Zhu, Qun Jin

ACM International Conference Proceeding Series 433 - 438 2020年02月 [査読有り]

担当区分：最終著者

DOI

Scopus
Applying of Adaptive Threshold Non-maximum Suppression to Pneumonia Detection

Hao Teng, Huijuan Lu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

Communications in Computer and Information Science 1160 CCIS 518 - 528 2020年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
IEEE access special section editorial: Proximity service (prose) challenges and applications

Yufeng Wang, Qun Jin, Jianhua Ma, Klimis Ntalianis, M. D. Zakirul Alam Bhuiyan, Michele Luvisotto

IEEE Access 8 169106 - 169109 2020年 [招待有り]

DOI

Scopus
Analyzing the Effects of Driving Experience on Prebraking Behaviors Based on Data Collected by Motion Capture Devices

Bo Wu, Yishui Zhu, Shoji Nishimura, Qun Jin

IEEE Access 8 197337 - 197351 2020年 [査読有り]

担当区分：最終著者

DOI
Detection of Health Abnormality Considering Latent Factors Inducing a Disease

Kiichi Tago, Kosuke Takagi, Qun Jin

IEEE Access 8 139433 - 139443 2020年 [査読有り] [国際誌]

担当区分：最終著者, 責任著者

　概要を見る

Underlying latent factors may cause a person to feel unwell. As the influence of the latent factors increases, the person will become sick. It is difficult to directly measure the influence of latent factors on risk degrees. However, early symptoms of a disease may affect vital signs such as body temperature and blood pressure, which may be a result of the influence of the latent factors. Deep learning is often used to predict the onset of a disease owing to its high accuracy. However, the reliability of this method is limited because of its characteristics of a black-box model. In this study, we propose a new approach to detect health abnormality. We regard the degree of influence of latent factors as the risk of disease and detect health abnormality before the onset of the disease. In our approach, we used a combination of Structural Equation Modeling (SEM) and Hidden Markov Model (HMM). First, in SEM, a domain model was created, and the factor score was estimated based on the relationship between latent factors and the explicit variables influenced by the factors. Thereafter, risk degrees were quantified with HMM using the estimated factor scores, and abnormality was identified in terms of risk degree. Finally, our proposed method was compared with three baselines: PCA (principal component analysis)-based approach, deep learning, and no-degree estimation methods. The average recall of our method was 98.75%, almost the same as the baselines, and false positive rate (FPR) was 0.186%, lower than the baselines. In the five-fold cross-validation comparing with no-degree estimation method, the average accuracy and recall of our method were 99.7% and 98.3% respectively, and FPR was 0.045%, all much better than the baseline. Moreover, our approach can make the process of obtaining the result visible and help detect abnormality sensitively by setting the threshold according to the risk degree, which can contribute to early detection of a disease and improve the reliability of abnormality detection as well.

DOI
Learning misclassification costs for imbalanced classification on gene expression data

Huijuan Lu, Yige Xu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

BMC Bioinformatics 20 ( Suppl 25 ) 681 - 681 2019年12月 [査読有り] [国際誌]

担当区分：最終著者

DOI PubMed

Scopus

33

被引用数

(Scopus)
Classification of TCM pulse diagnoses based on pulse and periodic features from personal health data

K. Tago, H. Wang, Q. Jin

Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM) 2019年12月 [査読有り]

担当区分：最終著者, 責任著者

　概要を見る

(accepted)

DOI

Scopus

12

被引用数

(Scopus)
Guest Editorial: Special Issue on Human-Centric Cyber Social Computing

Qun Jin, Weimin Li, Song Guo, Sethuraman Panchanathan

IEEE Transactions on Computational Social Systems 6 ( 5 ) 1038 - 1040 2019年10月 [招待有り]

担当区分：筆頭著者

DOI

Scopus

1

被引用数

(Scopus)
Visualization design based on personal health data and persona analysis

Zhi Li, Qun Jin

Proceedings - IEEE 17th International Conference on Dependable, Autonomic and Secure Computing, IEEE 17th International Conference on Pervasive Intelligence and Computing, IEEE 5th International Conference on Cloud and Big Data Computing, 4th Cyber Science and Technology Congress, DASC-PiCom-CBDCom-CyberSciTech 2019 201 - 206 2019年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Improved mask R-CNN for lung nodule segmentation

Huanlan Yan, Huijuan Lu, Minchao Ye, Ke Yan, Yige Xu, Qun Jin

Proceedings - 10th International Conference on Information Technology in Medicine and Education, ITME 2019 137 - 141 2019年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

18

被引用数

(Scopus)
Culture-based Color Influence Paths Analysis by Using Eye-tracking Devices

B. Wu, S. Nishimura, Y. Zhu, Q. Jin

66 - 71 2019年08月 [査読有り] [国際共著]

担当区分：最終著者

DOI

Scopus

8

被引用数

(Scopus)
Polarity classification of tweets considering the poster's emotional change by a combination of Naive Bayes and LSTM

K. Tago, K.Takagi, Q. Jin

Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science 11619 579 - 588 2019年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
An efficient location recommendation scheme based on clustering and data fusion

W. Cai, Y. Wang, R. Lv, Q. Jin

Computers & Electrical Engineering (Elsevier) 77 ( 2019 ) 289 - 299 2019年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

22

被引用数

(Scopus)
User role identification based on social behavior and networking analysis for information dissemination

X. Zhou, B. Wu, Q. Jin

Future Generation Computer Systems (Elsevier) 96 639 - 648 2019年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

28

被引用数

(Scopus)
BRIM: An accurate electricity spot price prediction scheme-based bidirectional recurrent neural network and integrated market

Yiyuan Chen, Yufeng Wang, Jianhua Ma, Qun Jin

Energies 12 ( 11 ) 2241 - 2241 2019年06月 [査読有り]

担当区分：最終著者

DOI

Scopus

30

被引用数

(Scopus)
A Distributed Intelligent Hungarian Algorithm for Workload Balance in Sensor-Cloud Systems Based on Urban Fog Computing

J. Jiang, Y. Long, Y. Mei, T. Wang, Q. Jin

IEEE Access 7 77649 - 77658 2019年06月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者, 責任著者

DOI

Scopus

22

被引用数

(Scopus)
An accurate false data detection in smart grid based on residual recurrent neural network and adaptive threshold

Yufeng Wang, Wanjiao Shi, Qun Jin, Jianhua Ma

Proceedings - IEEE International Conference on Energy Internet, ICEI 2019 499 - 504 2019年05月 [査読有り]

DOI

Scopus

20

被引用数

(Scopus)
Human–computer cooperation for future computing

Byeong Seok Shin, Houcine Hassan, Qun Jin

Journal of Supercomputing 75 ( 4 ) 1747 - 1750 2019年04月 [招待有り]

担当区分：最終著者

DOI

Scopus
Experiment Design and Analysis of Cross-cultural Variation in Color Preferences Using Eye-tracking

B. Wu, S. Nishimura, Y. Zhu, Q. Jin

Proc.MUE2019 (The 13th International Conference on Multimedia and Ubiquitous Engineering), Xi’an, China 590 44 - 49 2019年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Analysis of health changes and the association of health indicators in the elderly using TCM pulse diagnosis assisted with ICT devices: a time series study

S. Zhou, S. Nishimura, A. Ogihara, Q. Jin

European Journal of Integrative Medicine (Elsevier) 27 105 - 113 2019年04月 [査読有り]

担当区分：最終著者

DOI

Scopus

10

被引用数

(Scopus)
An improved SSO algorithm for cyber-enabled tumor risk analysis based on gene selection

C. Ye, J. Pan, Q. Jin

Future Generation Computer Systems (Elsevier) 89 407 - 418 2019年03月 [査読有り]

担当区分：最終著者

DOI

Scopus

8

被引用数

(Scopus)
Design of a computational model for social learning support and analytics

N.Y. Yen, J.C. Hung, C.C. Chen, Q. Jin

Computers in Human Behavior (Elsevier) 92 547 - 561 2019年03月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
A Self-Adaptive Process Mining Algorithm Based on Information Entropy to Deal with Uncertain Data

Weimin Li, Yuting Fan, Wei Liu, Minjun Xin, Hao Wang, Qun Jin

IEEE Access 7 131681 - 131691 2019年 [査読有り]

担当区分：最終著者

DOI

Scopus

8

被引用数

(Scopus)
Random convolutional neural network based on distributed computing with decentralized architecture

Yige Xu, Huijuan Lu, Minchao Ye, Ke Yan, Zhigang Gao, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11956 LNCS 504 - 510 2019年 [査読有り]

担当区分：最終著者

DOI

Scopus
Personalization Recommendation Algorithm Based on Trust Correlation Degree and Matrix Factorization

W. Li, X. Zhou, S. Shimizu, M. Xin, J. Jiang, H. Gao, Q. Jin

IEEE Access 7 45451 - 45459 2019年 [査読有り] [国際誌] [国際共著]

担当区分：最終著者, 責任著者

DOI
Emerging Privacy Issues and Solutions in Cyber-Enabled Sharing Services: From Multiple Perspectives

K. Yan, W. Shen, Q. Jin, H. Lu

IEEE Access 7 26031 - 26059 2019年 [査読有り] [国際誌] [国際共著]

担当区分：責任著者

DOI

Scopus

22

被引用数

(Scopus)
Message from the ITME 2018 General Chairs

Qun Jin, Ning Jin, Enrico Haemmerle

Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018 xxviii 2018年12月 [招待有り]

担当区分：筆頭著者

DOI

Scopus
An Effective Feature Selection Scheme for Healthcare Data Classification Using Binary Particle Swarm Optimization

Yiyuan Chen, Yufeng Wang, Liang Cao, Qun Jin

Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018 703 - 707 2018年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

18

被引用数

(Scopus)
Correlation Analysis of Health and Traditional Chinese Medicine (TCM) Pulse Diagnosis for the Elderly Using Wearable Devices

Siyu Zhou, Atsushi Ogihara, Shoji Nishimura, Qun Jin

Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018 745 - 749 2018年12月 [査読有り]

担当区分：最終著者

DOI

Scopus
An undergraduate curriculum model for intelligence science and technology

Jingde Cheng, Runhe Huang, Qun Jin, Jianhua Ma, Yi Pan

Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 234 - 239 2018年12月 [査読有り]

DOI

Scopus

1

被引用数

(Scopus)
Welcome message from the IEEE IoP 2018 general chairs

Guojun Wang, Hakim Mabed, Qun Jin, Bin Guo, Fuhua Oscar Lin

Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 xciii 2018年12月 [招待有り]

DOI

Scopus
TNERec: Topic-aware network embedding for scientific collaborator recommendation

Xiangjie Kong, Mengyi Mao, Jiaying Liu, Bo Xu, Ruihe Huang, Qun Jin

Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 1007 - 1014 2018年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

15

被引用数

(Scopus)
DNN-Based image classification for software GUI testing

Huijuan Lu, Li Wang, Minchao Ye, Ke Yan, Qun Jin

Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 1818 - 1823 2018年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Vote Parallel SVM: An extension of parallel support vector machine

Yan Song, Qun Jin, Ke Yan, Huijuan Lu, Julong Pan

Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 1942 - 1947 2018年12月 [査読有り]

DOI

Scopus

3

被引用数

(Scopus)
Modeling of cross-disciplinary collaboration for potential field discovery and recommendation based on scholarly big data

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Xuesong Xu, Qun Jin

87 591 - 600 2018年10月 [査読有り]

担当区分：最終著者

DOI

Scopus

43

被引用数

(Scopus)
An Anti-Noise Process Mining Algorithm Based on Minimum Spanning Tree Clustering

Li Weimin, Zhu Heng, Liu Wei, Chen Dehua, Jiang Jiulei, Jin Qun

IEEE ACCESS 6 48756 - 48764 2018年10月 [査読有り] [国際誌] [国際共著]

担当区分：最終著者

DOI

Scopus

18

被引用数

(Scopus)
Special Issue on Trends and Research Issues of Emerging Technologies to Enhance Learning

Yin Chengjiu, Yen Neil, Jin Qun

INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES 16 ( 4 ) 2018年10月 [招待有り]

担当区分：最終著者
Experiment and Analysis on Visual Field and Fixation when Going Upstairs and Downstairs

B. Wu, S. Nishimura, Q. Jin

Proc. ITME2018 (9th International Conference on Information Technology in Medicine and Education) 163 - 167 2018年10月 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
GCHAR: An efficient Group-based Context—aware human activity recognition on smartphone

Liang Cao, Yufeng Wang, Bo Zhang, Qun Jin, Athanasios V. Vasilakos

Journal of Parallel and Distributed Computing 118 67 - 80 2018年08月 [査読有り]

　概要を見る

With smartphones increasingly becoming ubiquitous and being equipped with various sensors, nowadays, there is a trend towards implementing HAR (Human Activity Recognition) algorithms and applications on smartphones, including health monitoring, self-managing system and fitness tracking. However, one of the main issues of the existing HAR schemes is that the classification accuracy is relatively low, and in order to improve the accuracy, high computation overhead is needed. In this paper, an efficient Group-based Context-aware classification method for human activity recognition on smartphones, GCHAR is proposed, which exploits hierarchical group-based scheme to improve the classification efficiency, and reduces the classification error through context awareness rather than the intensive computation. Specifically, GCHAR designs the two-level hierarchical classification structure, i.e., inter-group and inner-group, and utilizes the previous state and transition logic (so-called context awareness) to detect the transitions among activity groups. In comparison with other popular classifiers such as RandomTree, Bagging, J48, BayesNet, KNN and Decision Table, thorough experiments on the realistic dataset (UCI HAR repository) demonstrate that GCHAR achieves the best classification accuracy, reaching 94.1636%, and time consumption in training stage of GCHAR is four times shorter than the simple Decision Table and is decreased by 72.21% in classification stage in comparison with BayesNet.

DOI

Scopus

134

被引用数

(Scopus)
An Optimized trust model integrated with linear features for cyber-enabled recommendation services

Weimin Li, Jun Mo, Minjun Xin, Qun Jin

Journal of Parallel and Distributed Computing 118 81 - 88 2018年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

11

被引用数

(Scopus)
A Novel Personalized Recommendation Algorithm Based on Trust Relevancy Degree

W. Li, H. Zhu, X. Zhou, S. Shimizu, M. Xin, Q. Jin

Proc. CyberSciTech 2018 (2018 IEEE Cyber Science and Technology Congress) 418 - 422 2018年08月 [査読有り]

担当区分：最終著者

DOI

Scopus
TSP: Truthful Grading-Based Strategyproof Peer Selection for MOOCs

Yufeng Wang, Hui Fang, Chonghu Cheng, Qun Jin

Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 679 - 684 2018年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
PDL: An Efficient Prediction-Based False Data Injection Attack Detection and Location in Smart Grid

Wanjiao Shi, Yufeng Wang, Qun Jin, Jianhua Ma

Proceedings - International Computer Software and Applications Conference 2 676 - 681 2018年06月 [査読有り]

DOI

Scopus

23

被引用数

(Scopus)
BLE Mesh: A Practical Mesh Networking Development Framework for Public Safety Communications

Zhang Bo, Wang Yufeng, Wei Li, Jin Qun, Vasilakos Athanasios V

TSINGHUA SCIENCE AND TECHNOLOGY 23 ( 3 ) 333 - 346 2018年06月 [査読有り]

DOI

Scopus

10

被引用数

(Scopus)
Analyzing influence of emotional tweets on user relationships using Naive Bayes and dependency parsing

Kiichi Tago, Kosuke Takagi, Seiji Kasuya, Qun Jin

World Wide Web 22 ( 3 ) 1 - 16 2018年05月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

13

被引用数

(Scopus)
Special issue on communication and computation cooperation (3C): Principles, algorithms and systems

Kezhi Wang, Qun Jin, Hamid Sharif

International Journal of Communication Systems 31 ( 7 ) 2018年05月 [招待有り]

DOI

Scopus
Analyzing the changes of health condition and social capital of elderly people using wearable devices

Zhou Siyu, Ogihara Atsushi, Nishimura Shoji, Jin Qun

HEALTH INFORMATION SCIENCE AND SYSTEMS 6 ( 1 ) 4 - 4 2018年04月 [査読有り] [国際誌]

担当区分：最終著者

DOI PubMed

Scopus

27

被引用数

(Scopus)
Special issue on "Advances in human-like intelligence towards next-generation web"

Yen Neil, Hsu Ching-Hsien, Jin Qun, Kao Odej

NEUROCOMPUTING 279 1 - 2 2018年03月 [招待有り]

DOI

Scopus

2

被引用数

(Scopus)
Optimization modeling and analysis of trustworthiness determination strategies for service discovery of MSNP

Xixi Ma, Qun Jin, Julong Pan, Yufeng Wang

Journal of Supercomputing 75 ( 4 ) 1 - 17 2018年02月 [査読有り]

担当区分：責任著者

DOI

Scopus

3

被引用数

(Scopus)
Geo-QTI: A quality aware truthful incentive mechanism for cyber–physical enabled Geographic crowdsensing

Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

Future Generation Computer Systems 79 447 - 459 2018年02月 [査読有り]

　概要を見る

Nowadays, the cyber, social and physical worlds are increasingly integrating and merging. Especially, combining the strengths of humans and machines helps tackle increasing hard tasks that neither can be done alone. Following this trend, this paper designs a Quality aware Truthful Incentive mechanism for cyber–physical enabled Geographic crowdsensing called Geo-QTI. Different from existing work, Geo-QTI appropriately accommodates the utilities of various stakeholders: requesters, participants and the crowdsourcing platform, and explicitly takes the requesters’ quality requirements, and participants’ quality provision into account. Geo-QTI explicitly includes four components: requester selection, participant selection, pricing and allocation. Requester selection with feasible analysis removes the requesters whose job cannot be completed by all participants or suffers from the monopoly participant (without the participant's contribution, others cannot cover requesters’ requirement), obtains winning requesters set and determines actual payments. In participant selection phase, the platform aggregates the requested tasks (submitted by all winning requesters) in the sensed geographic area, and chooses the appropriate participants satisfying the winning requesters’ quality requirements with total cost as low as possible. Pricing phase determines the payments to winning participants. The phase of allocation assigns the specific participants to minimally cover the quality requirements of those winning requesters. Rigid theoretical analysis demonstrates Geo-QTI can achieve both requesters’ and participants’ individual rationality and truthfulness, computational efficiency and budget balance for the platform. Furthermore, the extensive simulations confirm our theoretical analysis, and illustrate that Geo-QTI can reduce requesters’ expenses greatly and ensure the fairness of allocation.

DOI

Scopus

9

被引用数

(Scopus)
Overlap community detection using spectral algorithm based on node convergence degree

Weimin Li, Shu Jiang, Qun Jin

Future Generation Computer Systems 79 408 - 416 2018年02月 [査読有り]

担当区分：最終著者

DOI

Scopus

30

被引用数

(Scopus)
Influence analysis of emotional behaviors and user relationships based on Twitter data

Kiichi Tago, Qun Jin

Tsinghua Science and Technology 23 ( 1 ) 104 - 113 2018年02月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

34

被引用数

(Scopus)
RankwithTA: A robust and accurate peer grading mechanism for MOOCs

Hui Fang, Yufeng Wang, Qun Jin, Jianhua Ma

Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017 2018- 497 - 502 2018年01月 [査読有り]

　概要を見る

Massive Online Open Courses (MOOCs) have the potential to revolutionize higher education with their wide outreach and accessibility. One of key challenges in MOOCs is the student evaluation: The large number of students makes it infeasible for instructors or teaching assistants (TAs) to grade all assignments. Peer grading-having students assess each other-is a promising approach to tackling the problem of evaluation at scale. The user evaluations are then used directly, or aggregated into a consensus value. However, lacking an incentive scheme, users have no motive in making effort in completing the evaluations, providing inaccurate answers instead. To address the above issues, we propose and implement a peer grading scheme, RankwithTA. Specifically, considering that the quality of a student determines both her performance in the assignment and her grading ability, RankwithTA makes the grade each student received depend on both the quality of the solution they submitted, and on the quality of their review and grading work to incentivize students' correct grading, Furthermore, the ground truth is incorporated, which utilizes external calibration by having some students graded by instructors or TAs to provide a basis for accuracy. The simulation results illustrate that RankwithTA performs better than the existing schemes.

DOI

Scopus

6

被引用数

(Scopus)
Learning misclassification costs for imbalanced datasets, application in gene expression data classification

Huijuan Lu, Yige Xu, Minchao Ye, Ke Yan, Qun Jin, Zhigang Gao

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10954 LNCS 513 - 519 2018年 [査読有り]

DOI

Scopus

1

被引用数

(Scopus)
Analysis of pulse diagnosis data from a TCM doctor and a device by Random Forest

K. Tago, A. Ogihara, S. Nishimura, Q. Jin

Kojima K., Sakamoto M., Mineshima K., Satoh K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer Science, Springer 11717 74 - 80 2018年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

4

被引用数

(Scopus)
Detection of Anomaly Health Data by Specifying Latent Factors with SEM and Estimating Hidden States with HMM

K. Tago, Q. Jin

Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education 137 - 141 2018年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
i-Blockchain: A Blockchain-Empowered Individual-Centric Framework for Privacy-Preserved Use of Personal Health Data

K. Ito, K. Tago, Q. Jin

Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education 829 - 833 2018年 [査読有り]

担当区分：最終著者

DOI

Scopus

30

被引用数

(Scopus)
Extraction of Factors Related to Transportations and Destinations by Decision Trees for Personal Whereabouts Modeling

S. Kasuya, K. Tago, Q. Jin

Proceedings of the 9th IEEE International Conference on Information Technology in Medicine and Education 808 - 812 2018年 [査読有り]

担当区分：最終著者

DOI

Scopus
Comparison of measurements by the betweenness centrality and subjective experiment on the word priority of Tweets

K. Takagi, K. Tago, K. Ito, Q. Jin

Proceedings of the 4th IEEE International Conference on Internet of People 1936 - 1941 2018年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Specifying Latent Factors with a Domain Model for Personal Data Analysis

K. Tago, K. Takagi, K. Ito, Q. Jin

Proceedings of the 3rd IEEE Cyber Science and Technology Congress (CyberSciTech) 1 - 6 2018年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Analysis of Health and Physiological Index Based on Sleep and Walking Steps by Wearable Devices for the Elderly

Siyu Zhou, Atsushi Ogihara, Shoji Nishimura, Qun Jin

Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017 2017- 245 - 250 2017年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Trust-Aware Recommendation for E-Commerce Associated with Social Networks

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017 2017- 211 - 216 2017年12月 [査読有り]

担当区分：最終著者

DOI

Scopus
Analyzing Influence of Emotional Tweets on User Relationships by Naive Bayes Classification and Statistical Tests

Kiichi Tago, Qun Jin

Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017 2017- 217 - 222 2017年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
A data intensive heuristic approach to the two-stage streaming scheduling problem

Wei Liang, Chunhua Hu, Min Wu, Qun Jin

JOURNAL OF COMPUTER AND SYSTEM SCIENCES 89 64 - 79 2017年11月 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Highly-skilled heath care workers exhibit tacit knowledge and advanced skills for preventing disordered swallowing and aspiration pneumonia in their patients

Nao Ueda, Manabu Yamaji, Moyuan Li, Kohei Matsushita, Qun Jin, Shoji Nishimura, Atsushi Ogihara

INTERNATIONAL JOURNAL OF ANTIMICROBIAL AGENTS 50 S159 - S159 2017年11月 [査読有り]
ActiRecognizer: Design and Implementation of a Real-Time Human Activity Recognition System

Liang Cao, Yufeng Wang, Qun Jin, Jianhua Ma

2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) 2018-January 266 - 271 2017年10月 [査読有り] [国際共著]

　概要を見る

In our society, inadequate physical activity is one of severe problems issues for human health, which may increase the health risks of many diseases. Nowadays, smartphones are ubiquitous and widely used around the world, in which multi-functional sensors and wireless interfaces are embedded. Therefore, smartphone is viewed as an appropriate platform for real-time activity recognition to address these healthy problems by monitoring and detecting user's everyday activities. In this paper, unlike other wearable devices based applications (e.g., watches, bands, or clip-on devices), ActiRecognizer, a smartphone-based prototype of a real-time human activity recognition (HAR) is designed and implemented, in which a detailed activity report of individuals (i.e. a pie chart containing the proportion and duration of each activity) can be correspondingly generated based on the detected real-time activities. Specifically, ActiRecognizer adopts client/server (C/S) architecture. At client side, smartphone associated with each individual periodically uploads the accelerometer and gyroscope sensing data to server for activity recognition and monitoring. At serve side, HAR is composed of offline training phase and online activity recognition phase: In training phase, sensing data are collected to extract the desired features that can appropriately characterize behaviors, classification model is generated utilizing these features, and then the trained classification model is used to classify user activity in real time. Finally, detailed activity reports and statistics are available to the user via a secure web interface.

DOI
Recommendation for Cross-Disciplinary Collaboration Based on Potential Research Field Discovery

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017 349 - 354 2017年09月 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
ABT: An Effective Ability-Balanced Team Based Incentive Mechanism in Crowdsourcing System

Yufeng Wang, Jie Huang, Qun Jin, Jianhua Ma

Proceedings - 5th International Conference on Advanced Cloud and Big Data, CBD 2017 220 - 225 2017年09月 [査読有り]

　概要を見る

Crowdsourcing systems which rely on a great deal of crowdworkers to perform large quantities of microtasks, have been leveraged in a variety of applications. There are two factors affecting the productive output of each crowdworker. One is skill level, which is private information to each crowdworker, and another is her variable expended effort. In this paper, we construct and analyze a total-Ability-balanced team based incentive mechanism ABT, which can stimulate the strategic crowdworkers to truthfully report their ability levels, and according to crowdworkers' ability levels, form the competing teams. Specifically, a crowdworker with a certain skill level, is askedto choose a specificskill level (i.e., denoted as an ability threshold), and a basic payment scheme is designed to incentivize the crowdworker to truthfully report her ability level. Then, according to the chosen ability thresholds, crowdworkers are organized into total ability balanced teams to earn extra team bonus, which can further motivate crowdworkers to exert more efforts. Compared to team formation process where workers are randomly assigned to the same-scale teams and the pay per task model, our scheme ABT can improve the work efficiency.

DOI

Scopus

3

被引用数

(Scopus)
Device-to-Device based mobile social networking in proximity (MSNP) on smartphones: Framework, challenges and prototype

Yufeng Wang, Li Wei, Athanasios V. Vasilakos, Qun Jin

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 74 241 - 253 2017年09月 [査読有り]

担当区分：最終著者

DOI

Scopus

32

被引用数

(Scopus)
A hybrid feature selection algorithm for gene expression data classification

Huijuan Lu, Junying Chen, Ke Yan, Qun Jin, Yu Xue, Zhigang Gao

NEUROCOMPUTING 256 56 - 62 2017年09月 [査読有り]

　概要を見る

In the DNA microarray research field, the increasing sample size and feature dimension of the gene expression data prompt the development of an efficient and robust feature selection algorithm for gene expression data classification. In this study, we propose a hybrid feature selection algorithm that combines the mutual information maximization (MIM) and the adaptive genetic algorithm (AGA). Experimental results show that the proposing MIMAGA-Selection method significantly reduces the dimension of gene expression data and removes the redundancies for classification. The reduced gene expression dataset provides highest classification accuracy compared to conventional feature selection algorithms. We also apply four different classifiers to the reduced dataset to demonstrate the robustness of the proposed MIMAGA-Selection algorithm. (C) 2017 Elsevier B.V. All rights reserved.

DOI

Scopus

330

被引用数

(Scopus)
Health concerns: Self-disclosure and online behavior analysis

Ting Wang, Guangyu Piao, Julong Pan, Qun Jin

Proceedings - 2016 8th International Conference on Information Technology in Medicine and Education, ITME 2016 182 - 186 2017年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Message from the GreenCom-2017 General Chair

Rubem Pereira, Geyong Min, Qun Jin

Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017 2018-January xxvii 2017年07月 [招待有り]

担当区分：最終著者

DOI

Scopus
Preface

Juhong Christie Liu, Shoji Nishimura, Hai Zhang, Qun Jin

Proceedings - 6th International Conference of Educational Innovation Through Technology, EITT 2017 2018-March xiii 2017年07月 [招待有り]

担当区分：最終著者

DOI

Scopus
Social recommendation based on trust and influence in SNS environments

Weimin Li, Zhengbo Ye, Minjun Xin, Qun Jin

MULTIMEDIA TOOLS AND APPLICATIONS 76 ( 9 ) 11585 - 11602 2017年05月 [査読有り]

担当区分：最終著者

DOI

Scopus

16

被引用数

(Scopus)
A heuristic approach to discovering user correlations from organized social stream data

Xiaokang Zhou, Qun Jin

MULTIMEDIA TOOLS AND APPLICATIONS 76 ( 9 ) 11487 - 11507 2017年05月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

35

被引用数

(Scopus)
ELR-DC: An Efficient Recommendation Scheme for Location Based Social Networks

Ruheng Lv, Yufeng Wang, Qun Jin, Jianhua Ma

Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016 567 - 572 2017年05月 [査読有り]

　概要を見る

Location-based social networks (LBSNs) have recently attracted millions of mobile users to share their locations and location-related contents. With the increasing use of LBSNs, an efficient personalized recommendation service is required to recommend appropriate point of interests (POIs) to users. Traditional collaborative filtering (CF) based recommendation algorithms need go through all users in LBSN to recommend locations to the target user. Due to the fact that many users are irrelevant to the target user, these approaches perform poorly in accuracy and scalability. In this paper, we propose an Efficient Location Recommendation scheme based on Discrete particle swarm optimization (DPSO) and Collaborative filtering, called ELR-DC. This scheme efficiently detects communities with close internal ties and then conducts location recommendation in each community. Specifically, a similarity network among users is firstly constructed based on their check-in activities, which explicitly takes into account users' similarities of interest and active regions. Then, an improved merging DPSO algorithm (IMDPSO) is proposed to detect communities through utilizing the formed similarity network. Then, in each community, CF algorithm is applied to recommend Top-N locations to each user. Finally, we conduct a comprehensive performance evaluation on a large-scale datasets collected from Gowalla. Experimental results show that the proposed scheme have the superiority of the precision and efficiency over the existed CF algorithms.

DOI

Scopus

1

被引用数

(Scopus)
SmartFDS: Design and Implementation of Falling Detection System on Smartphones

Xiao Li, Yufeng Wang, Qicai Zhou, Qun Jin

Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016 402 - 405 2017年05月 [査読有り]

担当区分：最終著者

DOI

Scopus
Message from the CIT 2016 program chairs

Jiannong Cao, Qun Jin, Xiaodong Lin, Vincenzo Piuri

Proceedings - 2016 16th IEEE International Conference on Computer and Information Technology, CIT 2016, 2016 6th International Symposium on Cloud and Service Computing, IEEE SC2 2016 and 2016 International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2016 xv - xix 2017年03月 [招待有り]

DOI

Scopus
Mobile crowdsourcing: framework, challenges, and solutions

Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 29 ( 3 ) 2017年02月 [査読有り]

　概要を見る

Crowdsourcing is the generalized act of outsourcing tasks, traditionally performed by an employee or contractor, to a large group of Internet population through an open call. With the great development of smartphones with rich built-in sensors and multiple ratio interfaces, mixing smartphone-based mobile technologies and crowdsourcing offers significant flexibilities and leads to a new paradigm called mobile crowdsourcing (MCS), which can be fully explored for real-time and location-sensitive crowdsourced tasks. In this paper, we present a taxonomy for the MCS applications, which are explicitly divided as using human as sensors, and exploiting the wisdom of crowd (i.e., human intelligence). Moreover, two paradigms for mobilizing users in MCS are outlined: direct mode and word of mouth mode. A comprehensive MCS framework and typical workflow of MCS applications are proposed, which consist of nine functional modules, pertaining to three stakeholders in MCS: crowdsourcer, crowdworkers, and crowdsourcing platform. Then, we elaborate the MCS challenges including task management, incentives, security and privacy, and quality control, and summarize the corresponding solutions. Especially, from the viewpoints of various stakeholders, we propose the desired properties that an ideal MCS system should satisfy. The primary goal of this paper is to comprehensively classify and provide a summary on MCS framework, challenges, and possible solutions to highlight the MCS related research topics and facilitate to develop and deploy interesting MCS applications. Copyright (C) 2016 John Wiley & Sons, Ltd.

DOI

Scopus

56

被引用数

(Scopus)
Analyzing of research patterns based on a temporal tracking and assessing model

Wei Liang, Qun Jin, Zixian Lu, Min Wu, Chunhua Hu

PERSONAL AND UBIQUITOUS COMPUTING 20 ( 6 ) 933 - 946 2016年11月 [査読有り]

　概要を見る

Scientific research works conducted by researchers spread all over the world in every research field, which are hard to be tracked and quantified. Although there are many research works focused on scientific community discovery and researcher profiling, it is still a big challenge to track the research patterns and assess the research development for an individual researcher or a research group over time. In this study, we seek to model researchers' scientific activities and quantify their outcome during their research career. A temporal tracking and assessing model is introduced to represent the research development and quantify the scientific outcome for both an individual and a group along the time. Based on our model, a research topic analyzing approach is developed to extract the topics covered by a research group for the research pattern analysis. Furthermore, a latent research pattern discovering approach is proposed to depict how a research group's research works contributed by its members are discovered and visualized. The effectiveness of our approach is evaluated based on a real academic dataset.

DOI

Scopus

5

被引用数

(Scopus)
QuaCentive: a quality-aware incentive mechanism in mobile crowdsourced sensing (MCS)

Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

JOURNAL OF SUPERCOMPUTING 72 ( 8 ) 2924 - 2941 2016年08月 [査読有り]

　概要を見る

Today's smartphones with a rich set of cheap powerful embedded sensors can offer a variety of novel and efficient ways to opportunistically collect data, and enable numerous mobile crowdsourced sensing (MCS) applications. Basically, incentive is one of fundamental issues in MCS. Through appropriately integrating three popular incentive methods: reverse auction, reputation and gamification, this paper proposes a quality-aware incentive framework for MCS, QuaCentive, which, pertaining to all components in MCS, can motivate crowd to provide high-quality sensed contents, stimulate crowdsourcers to give truthful feedback about quality of sensed contents, and make platform profitable. Specifically, first, we utilize the reverse auction and reputation mechanisms to incentivize crowd to truthfully bid for sensing tasks, and then provide high-quality sensed contents. Second, in to encourage crowdsourcers to provide truthful feedbacks about quality of sensed data, in QuaCentive, the verification of those feedbacks are crowdsourced in gamification way. Finally, we theoretically illustrate that QuaCentive satisfies the following properties: individual rationality, cost-truthfulness for crowd, feedback-truthfulness for crowdsourcers, platform profitability.

DOI

Scopus

37

被引用数

(Scopus)
Message from the IoP 2015 leading chairs

Qun Jin, Lu Liu, Jianxin Li

Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015 xl 2016年07月 [招待有り]

担当区分：筆頭著者

DOI

Scopus
Modeling and analyzing of Research topic evolution associated with social networks of researchers

Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

International Journal of Distributed Systems and Technologies 7 ( 3 ) 42 - 62 2016年07月 [査読有り]

　概要を見る

Research trends keep evolving along the time with certain trackable patterns. Mining academic literature and discovering the latent research trends evolution is an interesting and important problem. Few of previous studies focusing on academic topic evolution modeling have addressed the temporal topic evolution patterns. In addition, researchers' profile and their social networks are valuable complementary to the research trends tracking. In this study, to analyze the underlying research trends evolution along with the scientific collaborations of researchers, a novel temporal research trends evolution model associated with researchers' social networks is proposed and built. Specifically, the detected research topics are classified into different clusters in each timeslot, and the evolution patterns are deduced among these topic clusters. The effectiveness of our approach is evaluated based on a real academic dataset. The experimental results can help users to discover the major research trends for specific fields. Besides, the tracked statuses of the corresponding scientific groups are helpful for searching research trends or finding collaboration opportunities according to researchers' different requirements.

DOI

Scopus

1

被引用数

(Scopus)
Energy-efficient localization and tracking on smartphones: Design principle and solutions

Yufeng Wang, Yuanting Bu, Qun Jin, Athanasios V. Vasilakos

ACM International Conference Proceeding Series 15-17- 29 - 35 2016年06月 [査読有り]

　概要を見る

In recent years, various location based services (LBS) have witnessed great development and are being prevalently used in our life. However, as the foundation of various LBS applications, localization consumes large energy of resource-constraint mobile terminals, especially on smartphones. This paper explicitly proposes three technical principles, substitution, adaption and collaboration to guide energy-efficient localization and tracking schemes on smartphones. Then several typical schemes in indoor or outdoor environments are respectively summarized and compared under the umbrella of those three principles. Moreover, the context-Assisting techniques are also discussed to design energy-efficient LBS applications. Finally, the quantitative metrics to measure the tradeoff between energy and localization performance are summarized. The primary goal of this paper is to comprehensively classify and provide a summary on the sporadic localization schemes (with energy-efficiency as main concern), possible solutions and tradeoffs, and facilitate to develop and deploy the energy-efficient LBS applications.

DOI

Scopus

1

被引用数

(Scopus)
An Integrated Incentive Framework for Mobile Crowdsourced Sensing

Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

TSINGHUA SCIENCE AND TECHNOLOGY 21 ( 2 ) 146 - 156 2016年04月 [査読有り]

　概要を見る

Currently, mobile devices (e.g., smartphones) are equipped with multiple wireless interfaces and rich built-in functional sensors that possess powerful computation and communication capabilities, and enable numerous Mobile Crowdsourced Sensing (MCS) applications. Generally, an MCS system is composed of three components: a publisher of sensing tasks, crowd participants who complete the crowdsourced tasks for some kinds of rewards, and the crowdsourcing platform that facilitates the interaction between publishers and crowd participants. Incentives are a fundamental issue in MCS. This paper proposes an integrated incentive framework for MCS, which appropriately utilizes three widely used incentive methods: reverse auction, gamification, and reputation updating. Firstly, a reverse-auction-based two-round participant selection mechanism is proposed to incentivize crowds to actively participate and provide high-quality sensing data. Secondly, in order to avoid untruthful publisher feedback about sensing-data quality, a gamification-based verification mechanism is designed to evaluate the truthfulness of the publisher's feedback. Finally, the platform updates the reputation of both participants and publishers based on their corresponding behaviors. This integrated incentive mechanism can motivate participants to provide high-quality sensed contents, stimulate publishers to give truthful feedback, and make the platform profitable.

DOI

Scopus

26

被引用数

(Scopus)
Special Issue on Mobile Social Networking and computing in Proximity (MSNP)

Yufeng Wang, Qun Jin, Athanasios V. Vasilakos

JOURNAL OF COMPUTER AND SYSTEM SCIENCES 82 ( 1 ) 91 - 92 2016年02月 [招待有り]

DOI

Scopus

2

被引用数

(Scopus)
Gradually Adaptive Recommendation Based on Semantic Mapping of Users’ Interest Correlations

J. Chen, Xiaokang Zhou, Q. Jin

International Journal of Communication Systems 29 ( 2 ) 341 - 361 2016年01月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

4

被引用数

(Scopus)
Security and Privacy Mechanisms for Sensor Middleware and Application in Internet of Things (IoT)

Namje Park, Hongxin Hu, Qun Jin

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2016 ( 1 ) 2965438 - 2965438 2016年 [招待有り]

担当区分：最終著者

DOI

Scopus

23

被引用数

(Scopus)
A Framework of Personal Data Analytics for Well-Being Oriented Life Support

Seiji Kasuya, Xiaokang Zhou, Shoji Nishimura, Qun Jin

ADVANCED MULTIMEDIA AND UBIQUITOUS ENGINEERING: FUTURE INFORMATION TECHNOLOGY, VOL 2 354 443 - 449 2016年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Perspectives on Cyber Science and Technology for Cyberization and Cyber-enabled Worlds

Jianhua Ma, Kim-Kwang Raymond Choo, Hui-Huang Hsu, Qun Jin, William Liu, Kevin Wang, Yufeng Wang, Xiaokang Zhou

2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC 1 - 9 2016年 [査読有り]

　概要を見る

Cyberization, as a new big trend following computerization and informatization, is the process of forming a new cyberworld and transforming our current physical, social and mental worlds into novel cyber-combined worlds. Cyber science, responding to the cyberization trend, aims to create a new collection of knowledge about these cyber-enabled worlds, and provide a way of discovering what is in the cyber-enabled worlds and how they work. Cyber science is concerned with the study of phenomena caused or generated by the cyberworld and cyberphysical, cyber-social and cyber-mental worlds, as well as the complex intertwined integration of cyber physical, social and mental worlds. It fuels advances in cyber technology, beyond the existing cyber related technologies. In this paper, after discussing the cyberization background and process, and explaining cyber science and technology, we present our visions and perspectives on new opportunities, essential issues and major challenges for cyber science and technology. We further describe cyber related technologies and closely related existing research areas, and envision future research directions, in terms of cyber physical, cyber social, cyber life, cyber intelligence and cyber security, which are five basic dimensions of cyber science and technology.

DOI

Scopus

12

被引用数

(Scopus)
Personal Data Analytics to Facilitate Cyber Individual Modeling

Xiaokang Zhou, Bo Wu, Qun Jin, Jianhua Ma, Weimin Li, Neil Y. Yen

2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC 39 - 46 2016年 [査読有り]

　概要を見る

The high development of emerging computing paradigms, such as Ubiquitous Computing, Mobile Computing, and Social Computing, has brought us a big change from all walks of our work, life, learning and entertainment. Especially, with the high accessibility of social networking services along with the increasingly pervasive use of portable wireless mobile computing devices, more and more populations have been engaged into this kind of integration of real physical world and cyber digital space, which can be called the hyper world. To help people live better in the highly developed information society, the so-called cyber-individual (Cyber-I), which is far beyond a user model or a software agent to assist a user, has been proposed to provide the most comprehensive digital entities for its corresponding Real-I in terms of the individual's experience, behavior, and thinking as well as his or her birth, growth, and death. In this study, we concentrate on the personal data analytics to facilitate the cyber individual modeling. Organic Stream is introduced to systematically organize and refine the personal stream data, which can help improve the data processing and management in the CI-Spine tier and CI-Pivot tier of Cyber-I. The DSUN (Dynamically Socialized User Networking) model is employed to better utilize the collective intelligence from a group of users, which can help improve the CI-Mind tier to make Cyber-I to become more robust. Based on these, we discuss the functional modules for the facilitation of cyber individual modeling. Finally, a scenario is given, and the experimental results are presented to demonstrate that the valuable outcomes from the personal analysis can be utilized to enrich the Cyber-I, and provide users with more suitable services.

DOI

Scopus

2

被引用数

(Scopus)
Message forwarding strategies in Device-to-Device based mobile social networking in proximity (MSNP)

Yufeng Wang, Jiabing Chen, Qun Jin, Jianhua Ma

2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC 69 - 74 2016年 [査読有り]

　概要を見る

Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones. Message forwarding/data routing in MSNP relies on the movement of individuals and their encounter opportunities to relay data to the destination, so-called store-carry-forward (SCF) mode. Due to lacking continuous network connectivity and must handle dynamic topology, message forwarding mechanism in MSNP is challenging. In recent years, exploiting MSNP users' social behaviours to forward message, have drawn tremendous interests. In this paper, we provide the taxonomy of social behaviour-based forwarding strategies, comprehensively summarize and compare various schemes, including location-based and encounter-based (further divided into social property based and community-based) strategies. Location-based strategies forward data to the individuals geographically closer to the destination, while encounter-based strategies forward data to the users more socially active through considering human interactions. Then, we present open issues in MSNP forwarding strategies and their potential solutions. The goal of this work is to provide deep understanding on SCF based message forwarding in MSNP which properly incorporate the individual's social characteristics, and bring new visions to MSNP research and applications.

DOI

Scopus

4

被引用数

(Scopus)
Overlap Community Detection Based On Node Convergence Degree

Weimin Li, Shu Jiang, HuaiKou Miao, Xiaokang Zhou, Qun Jin

2016 IEEE 14TH INTL CONF ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, 14TH INTL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING, 2ND INTL CONF ON BIG DATA INTELLIGENCE AND COMPUTING AND CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/DATACOM/CYBERSC 163 - 167 2016年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Personal Data Analytics for Well-Being Oriented Life Support: Experiment and Feasibility Study

Seiji Kasuya, Xiaokang Zhou, Shoji Nishimura, Qun Jin

ADVANCES IN DIGITAL TECHNOLOGIES 282 172 - 179 2016年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Ubi-Liven: A Human-Centric Safe and Secure Framework of Ubiquitous Living Environments for the Elderly

Qun Jin, Bo Wu, Shoji Nishimura, Atsushi Ogihara

2016 FOURTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD 2016) 304 - 309 2016年 [査読有り]

担当区分：筆頭著者

DOI
A Privacy-Preserving Incentive Scheme for Advertisement Dissemination in Vehicular Social Networks

Peipei Xiao, Yufeng Wang, Qun Jin, Jianhua Ma

2016 IEEE TRUSTCOM/BIGDATASE/ISPA 1741 - 1746 2016年 [査読有り]

　概要を見る

Recent years has witnessed a great progress in Vehicular Social Networks (VSNs), which is a particular class of vehicular ad hoc networks, characterized by social aspects and features, including human mobility and rational behaviors. Among various VSN applications, one of the most promising applications is the dissemination of commercial advertisement via car-to-RSU (rode side unit) and car-to-car communication. However, due to non-cooperative behavior of selfish nodes or malicious ones in the real-world scenario, such vehicular advertisement system can't be realized unless proper security and incentive mechanisms are taken into account. In this paper, the privacy concern is addressed by leveraging a PKI (Public Key Infrastructure) to provide secure incentives for cooperative nodes. The selfishness issue is solved through adopting Topology dependent Reward Mechanisms (TDRM). Preliminary theoretical and simulation results show that, besides incentivizing individuals' participation, the proposed scheme can increase participants' reward through their active contribution and solicitation, and moreover, is robust against users' misbehaviors, especially Sybil-attack.

DOI
Dynamic Community Mining and Tracking Based on Temporal Social Network Analysis

Xiaokang Zhou, Wei Liang, Bo Wu, Zixian Lu, Shoji Nishimura, Takashi Shinomiya, Qun Jin

2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT) 177 - 182 2016年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Energy-Efficient Architecture and Technologies for Device to Device (D2D) Based Proximity Service

Zhang Bo, Wang Yufeng, Jin Qun, Ma Jianhua

CHINA COMMUNICATIONS 12 ( 12 ) 32 - 42 2015年12月 [査読有り]

　概要を見る

Considering that modern mobile terminals possess the capability to detect users' proximity, and offer means to directly communicate and share content with the people in close area, Device-to-Device (D2D) based Proximity Services (Pro Se) have recently witnessed great development, which enable users to seek for and utilize relevant value in their physical proximity, and are capable to create numerous new mobile service opportunities. However, without a breakthrough in battery technology, the energy will be the biggest limitation for ProSe. Through incorporating the features of ProSe (D2D communication technologies, abundant built-in sensors, localization-dependent, and context-aware, etc.), this paper thoroughly investigates the energy-efficient architecture and technologies for ProSe from the following four aspects: underlying networking technology, localization, application and architecture features, context-aware and user interactions. Besides exploring specific energy-efficient schemes pertaining to each aspect, this paper offers a perspective for research and applications. In brief, through classifying, summarizing and optimizing the multiple efforts on studying, modeling and reducing energy consumption for ProSe on mobile devices, the paper would provide guide for developers to build energy-efficient ProSe.

DOI

Scopus

7

被引用数

(Scopus)
A Pagerank-Inspired Heuristic Scheme for Influence Maximization in Social Networks

Bo Zhang, Yufeng Wang, Qun Jin, Jianhua Ma

INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH 12 ( 4 ) 48 - 62 2015年10月 [査読有り]

　概要を見る

This article focused on seeking a new heuristic algorithm for the influence maximization problem in complex social networks, in which a small subset of individuals are intentionally selected as seeds to trigger a large cascade of further adoptions of a new behavior under certain influence cascade models. In literature, degree and other centrality-based heuristics are commonly used to estimate the influential power of individuals in social networks. The major issues with degree-based heuristics are twofold. First, those results are only derived for the uniform IC model, in which propagation probabilities on all social links are set as same, which is rarely the case in reality; Second, intuitively, an individual's influence power depends not only on the number of direct friends, but also relates to kinds of those friends, that is, the neighbors' influence should also be taken into account when measuring one's influential power. Based on the general weighted cascade model (WC), this article proposes Pagerank-inspired heuristic scheme, PRDiscount, which explicitly discounts the influence power of those individuals who have social relationships with chosen seeds, to alleviate the "overlapping effect" occurred in behavior diffusion. Then, the authors use both the artificially constructed social network graphs (with the features of power-law degree distribution and small-world characteristics) and the real-data traces of social networks to verify the performance of their proposal. Simulations illustrate that PRDiscount can advantage over the existing degree-based discount algorithm, Degree Discount, and achieve the comparable performance as greedy algorithm.

DOI

Scopus

12

被引用数

(Scopus)
HIC 2015 Chairs' welcome

Neil Y. Yen, Qun Jin

HIC 2015 - Proceedings of the 2015 International Workshop on Human-centric Independent Computing, co-located with HT 2015 iii 2015年09月 [招待有り]

担当区分：最終著者
Social Recommendation Algorithm Dynamically Adaptable to User Profiling for SNS

Weimin Li, Yikai Ni, Minye Wu, Zhengbo Ye, Qun Jin

Proceedings - 2014 2nd International Conference on Advanced Cloud and Big Data, CBD 2014 261 - 266 2015年08月 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Multi-dimensional attributes and measures for dynamical user profiling in social networking environments

Xiaokang Zhou, Wei Wang, Qun Jin

MULTIMEDIA TOOLS AND APPLICATIONS 74 ( 14 ) 5015 - 5028 2015年07月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

40

被引用数

(Scopus)
Participatory information search and recommendation based on social roles and networks

Bo Wu, Xiaokang Zhou, Qun Jin

MULTIMEDIA TOOLS AND APPLICATIONS 74 ( 14 ) 5173 - 5188 2015年07月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

7

被引用数

(Scopus)
Personalized fitting recommendation based on support vector regression

Weimin Li, Xunfeng Li, Mengke Yao, Jiulei Jiang, Qun Jin

HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES 5 ( 1 ) 2015年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

22

被引用数

(Scopus)
Special Issue on "Massive Open Online Courses (MOOCs)" PREFACE

Hung Jason C, Shih Timothy K, Jin Qun

INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES 13 ( 3 ) IV - VI 2015年07月 [招待有り]

担当区分：最終著者
Intelligent state machine for social ad hoc data management and reuse

Neil Y. Yen, Qun Jin, Joseph C. Tsai, James J. Park

MULTIMEDIA TOOLS AND APPLICATIONS 74 ( 10 ) 3521 - 3541 2015年05月 [査読有り]

　概要を見る

Recent advances in information technology have turned out World Wide Web to be the main platform for interactions where participants-users and corresponding events-are triggered. Although the participants vary in accordance with scenarios, a considerable size of data will be generated. This phenomenon indeed causes the complexity in information retrieval, management, and resuse, and meanwhile, turns down the value of this data. In this research, we attempt to achieve efficient management of user-generated data and its derivative contexts (i.e., social ad hoc data) for human supports. The correlations among data, contexts, and their hybridization are specifically concentrated. An intelligent state machine is proposed to outline the relations of data and contexts, and applied to further identify their usage scenarios. The performance and feasibility can be revealed by the experiments that were conducted on the data collected from open social networks (e.g., Facebook, Twitter, etc.) in the past few years with size around 500 users and 8,000,000 shared contents from them.

DOI

Scopus
Privacy protection for lbs in mobile environments: Progresses, issues and challenges

Julong Pan, Zhengwei Zuo, Zhanyi Xu, Qun Jin

International Journal of Security and its Applications 9 ( 1 ) 249 - 258 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
LIP3: A Lightweighted Fine-Grained Privacy-Preserving Profile Matching Mechanism for Mobile Social Networks in Proximity

Yufeng Wang, Xiaohong Chen, Qun Jin, Jianhua Ma

ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, ICA3PP 2015 9532 166 - 176 2015年 [査読有り]

　概要を見る

Recently, Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones, which enable actively/passively and continuously seek for relevant value in one's physical proximity, through direct communicating with other individuals within the communication range, without the support of centralized networking infrastructure. Specially, a user would like to find out and interact with some strangers with similar interest in vicinity through profile matching. However, in matching process, individuals always have to reveal their personal and private profiles to strangers, which conflicts with users' growing privacy concerns. To achieve privacy preserving profile matching (i.e., friend discovery), many schemes are proposed based on homomorphic and commutative encryption, which bring tremendous computation and communication overheads, and are not practical for the resource limited mobile devices in MSNP. In this paper we adapt Confusion Matrix Transformation (CMT) method to design a Lightweighted fIne-grained Privacy-Preserving Profile matching mechanism, LIP3, which can not only efficiently realize privacy-preserving profile matching, but obtain the strict measurement of cosine similarity between individuals, while other existing CMT-based schemes can only roughly estimate the matching value.

DOI

Scopus

2

被引用数

(Scopus)
Personalized Micro-Learning Support Based on Process Mining

Jian Chen, Yueqin Zhang, Jingyu Sun, Yongle Chen, Fuping Lin, Qun Jin

2015 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN MEDICINE AND EDUCATION (ITME) 511 - 515 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus

14

被引用数

(Scopus)
Service Discovery Based on Trustworthiness in MSNP: Major Issues, Potential Solutions, and Feasible Strategies

Xixi Ma, Qun Jin, Julong Pan, Yufeng Wang

2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY) 315 - 320 2015年 [査読有り]

　概要を見る

With the popularity of mobile Internet, smart phones and location-based services, Mobile Social Network in Proximity (MSNP) has attracted more and more attentions, for which trustworthy service discovery and its associated latency are two important issues. In this paper, after overviewing MSNP and trustworthiness for service discovery in MSNP, we discuss the major issues and potential solutions of trustworthy service discovery. We present trustworthiness determination strategies based on service provider candidates' past experience and current profile analysis to reduce the latency caused by trustworthiness computation for trustworthy service discovery in MSNP.

DOI

Scopus

1

被引用数

(Scopus)
HYChat: A hybrid interactive chat system for mobile social networking in proximity

Jinhang Zuo, Yufeng Wang, Qun Jin, Jianhua Ma

2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY) 471 - 477 2015年 [査読有り]

　概要を見る

Recently, mobile social networks in proximity (MSNP) has gained tremendous attentions, which explicitly explores the physical proximity of individuals, and greatly facilitates their face-to-face interactions through direct communications. Generally, Proximity awareness can be enabled with two methodologies: Over-The-Top (OTT), in which the centralized server determines the proximity based on users' location updates and interests, and intermediate the interactions between proximal users; Device-to-Device (D2D), which allows two devices in radio range to discovery and communicate directly. This paper designs and implements a novel hybrid interactive chatting system, HYChat, which integrates the merits of both methodologies: simultaneously support direct interaction through WiFi Direct when individuals are within each other's radio range; when detecting two devices are out of range of WiFi Direct (e.g., due to individual's movement), it will switch to online OTT mode automatically to continue the interactive chat. Specifically, two key challenges in HYChat are preliminarily solved in this paper: profile matching prior to establishing connection among devices (i.e., layer 2 profile matching), and the smooth switching between D2D and OTT modes. The prototype of HYChat on Android phones illustrates its effectiveness. In brief, the hybrid system HYChat could greatly facilitate individuals' social interaction in physical proximity.

DOI

Scopus

6

被引用数

(Scopus)
A Temporal Model of Research Work Tracking and Assessing for an Individual and a Group

Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY) 440 - 445 2015年 [査読有り]

　概要を見る

Although there are many research works focused on scientific community discovery and researcher profiling, it is still a challenge to track and assess the research development for an individual researcher or a research group over time. In this study, we seek to model and quantify an individual's research work outcome during his/her research career. A temporal tracking model is introduced to represent research development for both an individual and a group along the time. Furthermore, assessing measures are proposed to depict how to quantify a research group's outcomes by its members' contribution. Based on our model, a research topic analyzing approach is proposed to extract the topics covered by a group and discover the group's research pattern. The analyzed output is helpful for a researcher to pursue his/her scientific life or find collaboration opportunities.

DOI

Scopus

2

被引用数

(Scopus)
Open Learning Platform Based on Personal and Social Analytics for Individualized Learning Support

Xiaokang Zhou, Bo Wu, Qun Jin

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS 1741 - 1745 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Modeling of research topic evolution associated with social networks of researchers

Wei Liang, Zixian Lu, Qun Jin, Yonghua Xiong, Min Wu

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS 1169 - 1174 2015年 [査読有り]

　概要を見る

Understanding research topic evolution in a specific field is important to learn the temporal structure and latent research trends. Although research works in terms of topic analysis have been developed for many years, it is still difficult to well understand the topic evolution due to the limitation of the bibliographical data which does not consider the researchers' profiles and their social networks. In this study, to analyze the underlying research topic evolution and facilitate the scientific collaborations for researchers, a novel topic evolution model based on the analysis of researchers' social networks is built. Specifically, the researchers' co-authorships associated with their latent social networks are analyzed. A research topic tracking method is then developed to track the topic evolutions and analyze the research lifecycle for the latent scientific teams. The derived results can help users to discover the major research trends for specific fields. And the tracked statuses of the corresponding scientific groups are illustrated in different lifecycle stages, which is useful for the search of research trends or finding of collaboration opportunity according to researchers' different requirements.

DOI

Scopus

4

被引用数

(Scopus)
BWMesh: a multi-hop connectivity framework on Android for proximity service

Yufeng Wang, Jing Tang, Qun Jin, Jianhua Ma

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS 278 - 283 2015年 [査読有り]

　概要を見る

Considering the inherent properties of privacy protection and battery efficiency, Device-to-Device (D2D) based proximity service (ProSe) has recently witnessed great development, which enable user to continuously and passively search for and utilize relevant value in one's physical proximity, and is capable to create numerous new mobile service opportunities. However, most of existing ProSe enabled frameworks and applications only provide single-hop Peer-to-Peer connection, lack of easily supporting simultaneous and multi-hop connection on commercially available smartphones to broaden ProSe coverage in static scenario. To solve this issue, this paper proposes a multi-hop connectivity framework BWMesh, through combining Bluetooth and WiFi Direct technologies. BWMesh possesses two special features: exploit users' heterogeneous network and enable smooth interaction among devices with different wireless technologies; provide an easy-to-deploy multi-hop networking framework on currently commercial available smartphones. Specifically, we identify several key issues in multi-hop connectivity framework, design and implement corresponding components to deal with those issues. Then, a prototype MultiChat, is developed based on BWMesh framework, which enables real-time chat among users in proximity, in multi-hop way, without accessing to Internet.

DOI

Scopus

15

被引用数

(Scopus)
Mobile crowdsourcing: architecture, applications, and challenges

Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS 1127 - 1132 2015年 [査読有り]

　概要を見る

Crowdsourcing is the generalized act of outsourcing tasks, traditionally performed by employees or contractors, to a large group of Internet population (the wise crowd) by means of an open call. With the great development of smartphones with rich built-in sensors and ratio interfaces, mixing smartphone-based mobile technologies and crowdsourcing offers vast computing resources, and leads to a new paradigm called Mobile Crowdsourcing (MCS). In this paper, we presents a taxonomy for the MCS applications, which are explicitly divided as using human as sensors, and exploiting the wisdom of crowd, and typical applications are summarized and compared. Then, a generic MCS framework is proposed, which consists of multiple functional modules. Finally, we elaborate the challenges in MCS applications (i.e., quality control, task management, incentives, as well as security and privacy), and summarize potential solutions. Our main contribution is to classify and provide a summary MCS framework, challenges and possible solutions to facilitate to develop and deploy various MCS applications.

DOI

Scopus

11

被引用数

(Scopus)
Associative Recommendation of Learning Contents Aided by Eye-Tracking in a Social Media Enhanced Environment

Guangyu Piao, Xiaokang Zhou, Qun Jin

UBIQUITOUS COMPUTING APPLICATION AND WIRELESS SENSOR 331 493 - 501 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus
A Heuristic Scheduling Approach to Hybrid Makepsan Problem for Data Intensive Computing

Wei Liang, Yonghua Xiong, Min Wu, Qun Jin

2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY) 932 - 937 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Strategic management advanced service for sustainable computing environment

Sang Soo Yeo, Qun Jin, Vincenzo Loia, Hangbae Chang

Scientific World Journal 2015 1 - 2 2015年 [招待有り]

DOI

Scopus
Organic streams a unified framework for personal big data integration and organization towards social sharing and individualized sustainable use

Xiaokang Zhou, Qun Jin

Big Data: Algorithms, Analytics, and Applications 241 - 255 2015年01月 [査読有り]

担当区分：最終著者, 責任著者
Message from SocialCom 2015 general chairs

Qun Jin, Timothy K. Shih

Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015 xxx 2015年 [招待有り]

担当区分：筆頭著者

DOI

Scopus
Social network recommendation based on hybrid suffix tree clustering

Jianhao Zhang, Xun Ma, Weimin Li, Qun Jin

Lecture Notes in Electrical Engineering 330 47 - 53 2015年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Message from the FiSTA 2014 workshop organizers

Bernady O. Apduhan, Rafael Santos, Jianhua Ma, Qun Jin

Proceedings - 14th International Conference on Computational Science and Its Applications, ICCSA 2014 xxii 2014年12月 [招待有り]

担当区分：最終著者

DOI

Scopus
On studying business models in mobile social networks based on two-sided market (TSM)

Yufeng Wang, Jing Tang, Qun Jin, Jianhua Ma

JOURNAL OF SUPERCOMPUTING 70 ( 3 ) 1297 - 1317 2014年12月 [査読有り]

　概要を見る

In contrast to the huge popularity of Mobile Social Network (MSN) services, not sufficient attention has been reserved to the dynamics of revenue streams and business models in MSN. In this paper, we investigate how a two-sided market (TSM) formulation can be used to provide insight for the problem above from the perspective of MSN platform. Intuitively, MSN service platform could be described as a two-sided market, in which the critical feature is indirect value flow (indirect network externality): one/both sides of the market benefit from increasing adoption and/or consumption of the other side. For instance, participants, like consumers and the third service providers (or advertisers), are the "two sides" of MSN platform. In this paper, our contributions are threefold. First, we thoroughly characterize the economic features of MSN as TSM, including mobility, network externalities and herd effect, as well as long tail property. Second, we provide the various revenue streams within the framework of TSM, including advertising, subscription, and transactions, and characterize the basic components of general business model in MSN. Finally, the free plus premium (Freemium) business model in MSN is formally analyzed. Specifically, we quantitatively characterize the relationship of participation levels among free and premium users as well as service providers, and illustrate the mutual enhancement among those participants. And moreover, Freemium is theoretically compared with the traditional business model with no free users (NF model). The numerical results show that, in Freemium, the participation levels of premium users and service providers, as well as the profit of MSN platform always exceed the corresponding terms in NF model.

DOI

Scopus

9

被引用数

(Scopus)
Recommendation of location-based services based on composite measures of trust degree

Weimin Li, Mengke Yao, Xiaokang Zhou, Shoji Nishimura, Qun Jin

JOURNAL OF SUPERCOMPUTING 69 ( 3 ) 1154 - 1165 2014年09月 [査読有り]

担当区分：最終著者

DOI

Scopus

8

被引用数

(Scopus)
Survey on mobile social networking in proximity (MSNP): approaches, challenges and architecture

Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

WIRELESS NETWORKS 20 ( 6 ) 1295 - 1311 2014年08月 [査読有り]

　概要を見る

Recently, mobile social networks (MSN) have gained tremendous attention, which free users from face-to-monitor life, while still can share information and stay in touch with their friends on the go. However most MSN applications regard mobile terminals just as entry points to existing social networks, in which centralized servers (for storage and processing of all application/context data) and continual Internet connectivity are prerequisites for mobile users to exploit MSN services, even though they are within proximity area (like campus, event spot, and community, etc.), and can directly exchange data through various wireless technologies (e.g., Bluetooth, WiFi Direct, etc.). In this paper, we focus on mobile social networking in proximity (MSNP), which is explicitly defined in our paper as: MSNP is wireless peer-to-peer (P2P) network of spontaneously and opportunistically connected nodes, and uses geo-proximity as the primary filter in determining who is discoverable on the social network. In this paper, first, primary support approaches related to MSNP available in literature, are summarized and compared, including MSN, mobile P2P and opportunistic networks. And then, we offer the special characteristics of MSNP, open issues and potential solutions. A networking technologies and platform independent architecture is proposed for developing MSNP applications, and proof-of-concept implementation of WiFi direct based MSNP application is also provided. Our primary goal is to identify the characteristics, technical challenges and potential solutions for future MSNP applications, capable to flexibly adapt to different application domains and deployment requirements.

DOI

Scopus

67

被引用数

(Scopus)
Special Issue on "Hybrid intelligence for growing internet and its applications" Preface

Neil Y. Yen, Qun Jin, Ching-Hsien Hsu, Qiangfu Zhao

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE 37 401 - 403 2014年07月 [招待有り]

DOI

Scopus
Probability Modeling and Functional Validation of Dynamic Service Composition for Location Based Services with Uncertain Factors

Weimin Li, Zhengbo Ye, Xiaohua Zhao, Jiulei Jiang, Qun Jin

JOURNAL OF INTERNET TECHNOLOGY 15 ( 4 ) 635 - 643 2014年07月 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Process-Focused Social Learning Analytics Based on Personal Big Data for Cross-MOOCs Open Environments

Q. Jin, X. Zhou, B. Wu, J. Chen, J. Pan, W. Zheng

(Poster) Intel‐CSU Transparent Computing and Big Data Summit 2014年07月 [招待有り]

担当区分：筆頭著者
Special section on human-centric computing Preface

Qun Jin, Sethuraman Panchanathan, Changhoon Lee

INFORMATION SCIENCES 257 229 - 230 2014年02月 [招待有り]

担当区分：筆頭著者

DOI

Scopus
A human-centric framework for context-aware flowable services in cloud computing environments

Yishui Zhu, Roman Y. Shtykh, Qun Jin

INFORMATION SCIENCES 257 231 - 247 2014年02月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

13

被引用数

(Scopus)
A malicious behavior analysis based Cyber-I birth

Jie Wen, Jianhua Ma, Runhe Huang, Qun Jin, Jian Chen, Benxiong Huang, Ning Zhong

JOURNAL OF INTELLIGENT MANUFACTURING 25 ( 1 ) 147 - 155 2014年02月 [査読有り]

　概要を見る

Cyber-Individual (Cyber-I) is the digital counterpart of an individual in the real world, which aims at systematically studying and developing comprehensive individual human modeling and its associated applications. The ultimate goal of this research is to create a digital clone for each individual and to provide active desirable services. We present a part of our research work focusing on examining the basic system architecture and the birth process of Cyber-I from a security perspective. In this study, a customized honeypot is used to record multidimensional data Cyber-I is constructed for a corresponding invader. Further, assembling a Cyber-I with associated CI-Applications enables aninvader having more behaviors in the honeypot and provides a possible chance to prolong activities of the invader, which complements a loop mechanism to feed Cyber-I for its growth. The preliminary result in this paper reveals that appropriate authorization and controls are extremely necessary to prevent Cyber-I from being maliciously used and to ensure privacy of its real individual in building an open Cyber-I platform.

DOI

Scopus

3

被引用数

(Scopus)
User Attribute Analysis for Dynamical User Profiling in Social Networking Environments

X. Zhou, Q. Jin

Proc. AIM2014 (The 4th FTRA International Conference on Advanced IT, Engineering and Management) 2014年02月 [査読有り]

担当区分：最終著者
Personalized Fitting with Deviation Adjustment Based on Support Vector Regression for Recommendation

Weimin Li, Mengke Yao, Qun Jin

MULTIMEDIA AND UBIQUITOUS ENGINEERING 308 173 - 178 2014年 [査読有り]

担当区分：最終著者

DOI

Scopus
Hierarchical Modeling and Analysis of Social Roles for Collective Decision-Making Support

Bo Wu, Xiaokang Zhou, Qun Jin, Fuhua Lin, Henry Leung

2014 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (CIT) 490 - 495 2014年 [査読有り]

　概要を見る

With the popularity of Social Network Service (SNS) and the increasing of users, individuals' social roles in a social network have become more and more important in recommendation of the personalized services, and in a collective decision-making process as well. In an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may be multifarious. In this study, we consider users' social roles as an important element to support the collective decision-making process. After introducing the social choice theories and collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way, and utilize it to support the collective decision-making process. A case study for COD (Course-Offering Determination) with an application scenario is demonstrated to show the process of how users' social roles are utilized to support the collective decision-making.

DOI

Scopus

1

被引用数

(Scopus)
A Wi-Fi Direct based P2P application prototype for mobile social networking in proximity (MSNP)

Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

2014 IEEE 12TH INTERNATIONAL CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING (DASC)/2014 IEEE 12TH INTERNATIONAL CONFERENCE ON EMBEDDED COMPUTING (EMBEDDEDCOM)/2014 IEEE 12TH INTERNATIONAL CONF ON PERVASIVE INTELLIGENCE AND COMPUTING (PICOM) 283 - + 2014年 [査読有り]

　概要を見る

Nowadays, most popular social networking services adopt centralized architecture, in which continual Internet connectivity is prerequisite for each user to exploit those services, and centralized servers are used for storage and processing of all application/context data, even though mobile users are within proximity area (like campus, event spot, and community), and can directly exchange media through various wireless technologies (e.g., Bluetooth, Wi-Fi Direct, etc.). On one hand, the omniscient centralized server may cause serious privacy concern, due to the fact that it collects and stores all users' data (messages, profiles, location, relations, etc.); On the other hand, transmitting a large amount of media generated by users in proximity through Internet, would not only bring a lot of pressure to the network infrastructure and service provider, but incur heavy data traffic cost to users. In this paper, our contributions are twofold. First, we propose a Wi-Fi Direct based P2P social networking framework, which enables direct data exchange among users without using infrastructure network when users are located in proximity, and provide solutions to two core problems in this framework, i.e., discoverability and privacy. Second, the prototype of this framework is preliminarily implemented in Android, which is composed of the following functions: localization based on Google Geocoding, Chat, and file-sharing component supporting intermittent transmission.

DOI

Scopus

12

被引用数

(Scopus)
A Management System for Cyber Individuals and Heterogeneous Data

Jun Ren, Jianhua Ma, Runhe Huang, Qun Jin, Zhigang Chen

2014 IEEE 11TH INTL CONF ON UBIQUITOUS INTELLIGENCE AND COMPUTING AND 2014 IEEE 11TH INTL CONF ON AUTONOMIC AND TRUSTED COMPUTING AND 2014 IEEE 14TH INTL CONF ON SCALABLE COMPUTING AND COMMUNICATIONS AND ITS ASSOCIATED WORKSHOPS 88 - 95 2014年 [査読有り]

　概要を見る

The progressive development of information and communication technologies has led us to a new world called hyper world that is composed by the cyber world and the physical world, which, at the same time, brings us the digital explosions of data and connectivity as well as all kinds of smart services. Based on these, Cyber-I was proposed, which aims at creating a unique, digital, comprehensive description for every real person so that the possibility for the person being in the cyber world to get lost in the digital explosions will be reduced. However, the ultimate goal of realizing such Cyber-I needs an endless research process, which will cover multiple areas and disciplines. In order to merge efforts on the study of Cyber-I together as well as provide people with better services utilizing Cyber-I, this paper presents our research and development on a Cyber-I oriented management system where (1) the life cycle of Cyber-I including its birth, growth and death is simulated, (2) with the NO-SQL properties supported by Mongo DB, heterogeneous personal data coming from disparate sources with different formats through varied media can be managed in a scalable way, and (3) apps connected with the Cyber-I can not only fetch personal data but also provide personalized services, while the collected personal data can be used to generate user models from different aspects.

DOI

Scopus

10

被引用数

(Scopus)
Alljoyn based direct proximity service development: overview and prototype

Yufeng Wang, Li Wei, Qun Jin, Jianhua Ma

2014 IEEE 17th International Conference on Computational Science and Engineering (CSE) 634 - 641 2014年 [査読有り]

　概要を見る

Proximity awareness, the ability to actively (or passively) and continuously search for relevant value in one's physical proximity, is at the core of mobile revolution that is changing the way we interact with people and things around us. Especially, Device-to-Device (D2D) (peer-to-peer (P2P)) solutions support infrastructure-free and self-organized proximity services, and have great commercial potential from application viewpoint. However, astonishingly, the glaring absence of the practical and easy-to-use proximity service development framework is alarming. This paper aims at investigating the Qualcomm AllJoyn middleware, an open source peer-to-peer software development framework for ad-hoc proximity based D2D communication, and exploring how this middleware can enable the development of distributed application in mobile social networks in proximity (MSNP). Specifically, we thoroughly overview the core concepts and basic components in AllJoyn framework, and summarize the typical workflow of developing AllJoyn based proximity application. Furthermore, an AllJoyn based MSNP prototype, AllChat, is designed and implemented, in which users can enjoy text chat and photo sharing with both group and peer interaction modes in real time.

DOI

Scopus

16

被引用数

(Scopus)
Social Stream Organization Based on User Role Analysis for Participatory Information Recommendation

Xiaokang Zhou, Bo Wu, Qun Jin, Shoji Nishimura, Julong Pan, Wenbin Zheng, Jianhua Ma

2014 7TH INTERNATIONAL CONFERENCE ON UBI-MEDIA COMPUTING AND WORKSHOPS (UMEDIA) 105 - 110 2014年 [査読有り]

　概要を見る

In this study, we propose an integrated approach to organize and refine the social streams in accordance with the analysis of both social data and social roles within a social group. The social stream data will be first collected and organized based on users' individual needs. After the calculation and analysis of users' importance based on the identification and classification of users' dynamical social roles within a user group, a mechanism is developed to organize and refine social streams and further provide users with more suitable and useful information that best fits their needs from more related users, in order to better assist the participatory information search and recommendation process in the social networking environment.

DOI

Scopus

4

被引用数

(Scopus)
Message from the ITME 2013 general chairs

Yongnian Liu, Xiaohong Jiang, James J. Park, Qun Jin, Hong Liu

Lecture Notes in Electrical Engineering 269 2014年 [招待有り]
Preface

Qun Jin, Jason C. Hung

International Journal of Computational Science and Engineering 9 ( 3 ) 153 - 154 2014年 [招待有り]

担当区分：筆頭著者

DOI

Scopus
A progressive approach for cross-browser web data generation

Jin Zhu, Yoshiyori Urano, Hidenori Nakazato, Qun Jin

International Journal of Computational Science and Engineering 9 ( 3 ) 235 - 246 2014年 [査読有り]

担当区分：最終著者

DOI

Scopus
A probabilistic timing constraint modeling and functional validation approach to dynamic service composition for LBS

Weimin Li, Xiaohua Zhao, Jiulei Jiang, Xiaokang Zhou, Qun Jin

Lecture Notes in Electrical Engineering 274 501 - 508 2014年 [査読有り]

担当区分：最終著者

DOI

Scopus
An integrated recommendation approach based on influence and trust in social networks

Weimin Li, Zhengbo Ye, Qun Jin

Lecture Notes in Electrical Engineering 309 83 - 89 2014年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Capturing unselfconscious information seeking behavior by analyzing gaze patterns via eye tracking experiments

Guangyu Piao, Xiaokang Zhou, Qun Jin, Shoji Nishimura

2013 IEEE Conference Anthology, ANTHOLOGY 2013 2014年 [査読有り]

　概要を見る

In recent years, eye tracking has been widely applied in a variety of fields, such as web usability studies and psychological experiments. To develop a personalized system or network service, it is important to recognize and capture users' needs, situations and contexts in order to create an effective user model. In this paper, we present an integrated approach on how to capture users' unselfconscious information seeking behavior by analyzing their gaze patterns using an eye tracker. We describe the design of an eye tracking experiment, and analyze the eye tracking data to extract gaze patterns, which can be used for use modeling. We further discuss the experiment result and highlight our future work. © 2013 IEEE.

DOI

Scopus
Blended learning support with social media empowered by ubiquitous personal study

Xiaokang Zhou, Haifeng Man, Hong Chen, Yan Wu, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7697 130 - 139 2014年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Analysis of sharable learning processes and action patterns for adaptive learning support

Xiaokang Zhou, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8613 173 - 178 2014年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus
Recommendation of optimized information seeking process based on the similarity of user access behavior patterns

Jian Chen, Xiaokang Zhou, Qun Jin

PERSONAL AND UBIQUITOUS COMPUTING 17 ( 8 ) 1671 - 1681 2013年12月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

20

被引用数

(Scopus)
Modeling user-generated contents: an intelligent state machine for user-centric search support

Neil Y. Yen, James J. (Jong Hyuk) Park, Qun Jin, Timothy K. Shih

PERSONAL AND UBIQUITOUS COMPUTING 17 ( 8 ) 1731 - 1739 2013年12月 [査読有り]

　概要を見る

Researchers tend to agree that an increasing quantity of data has caused the complexity and difficulty for information discovery, management, and reuse. An essential factor relates to the increasing channels (i.e., Internet, social media, etc.) for information sharing. Finding information, especially those meaningful or useful one, that meets ultimate goal (or task) of user becomes harder then it is used to be. In this research, issues concerning the use of user-generated contents for individual search support are investigated. In order to make efficient use of user-generated contents, an intelligent state machine, as a hybridization of graph model (Document Graph) and petri-net model (Document Sensitive Petri-Net), is proposed. It is utilized to clarify the vague usage scenario between user-generated contents, such as discussions, posts, etc., and to identify correlations and experiences within them. As a practical contribution, an interactive search algorithm that generates potential solutions for individual is implemented. The feasibility of this research is demonstrated by a series of experiments and empirical studies with around 350,000 user-generated contents (i.e., documents) collected from the Internet and 200 users.

DOI

Scopus

4

被引用数

(Scopus)
Research on life-cycle of user model in U-Business

Bofeng Zhang, Jianxing Zheng, Jianhua Ma, Yinsheng Li, Guobing Zou, Qun Jin

PERSONAL AND UBIQUITOUS COMPUTING 17 ( 7 ) 1449 - 1457 2013年10月 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Intelligent route generation: Discovery and search of correlation between shared resources

Neil Y. Yen, Runhe Huang, Jianhua Ma, Qun Jin, Timothy K. Shih

International Journal of Communication Systems 26 ( 6 ) 732 - 746 2013年06月 [査読有り]

　概要を見る

Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes it possible for learning participants to be engaged in an open and connected social environment, and also allows the learning activities to be performed at any time and any place. In this study, the discovery of correlation among shared resources is concentrated. A hypothetical scenario is considered that the information, such as photos and thoughts, is applicable to be shared with implicit context (i.e., geographical information) by learners through a practical implementation, PadSCORM, on a mobile device. Two major contributions are achieved. First, the correlations among resources are determined through usage experiences mining and geographical information adjustment. It then assists learners in filtering out redundant information by highlighting the significance of resources. Second, an intelligent searching algorithm is proposed to visualize adaptive routes to facilitate search process and to enrich the learning activity. The empirical experiments revealing the feasibility and performance (e.g., accuracy and effectiveness) are conducted in the universities in North Taiwan. © 2012 John Wiley &amp
Sons, Ltd.

DOI

Scopus

14

被引用数

(Scopus)
Enriching user search experience by mining social streams with heuristic stones and associative ripples

Xiaokang Zhou, Neil Y. Yen, Qun Jin, Timothy K. Shih

Multimedia Tools and Applications 63 ( 1 ) 129 - 144 2013年03月 [査読有り]

　概要を見る

Recently, social networking sites such as Facebook and Twitter are becoming increasingly popular. The high accessibility of these sites has allowed the so-called social streams being spread across the Internet more quickly and widely, as more and more of the populations are being engaged into this vortex of the social networking revolution. Information seeking never means simply typing a few keywords into a search engine in this stream world. In this study, we try to find a way to utilize these diversified social streams to assist the search process without relying solely on the inputted keywords. We propose a method to analyze and extract meaningful information in accordance with users' current needs and interests from social streams using two developed algorithms, and go further to integrate these organized stream data which are described as associative ripples into the search system, in order to improve the relevance of the results obtained from the search engine and feedback users with a new perspective of the sought issues to guide the further information seeking process, which can benefit both search experience enrichment and search process facilitation. © 2012 Springer Science+Business Media, LLC.

DOI

Scopus

26

被引用数

(Scopus)
Effective session key distribution for secure fast handover in mobile networks (vol 44, pg 97, 2010)

Jong Hyuk Park, Qun Jin

TELECOMMUNICATION SYSTEMS 52 ( 1 ) 359 - 359 2013年01月 [査読有り]

担当区分：最終著者

DOI

Scopus
Discovery of action patterns in task-oriented learning processes

Xiaokang Zhou, Jian Chen, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8167 121 - 130 2013年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

5

被引用数

(Scopus)
Eye-Tracking Experiment Design for Extraction of Viewing Patterns in Social Media

Guangyu Piao, Qun Jin, Xiaokang Zhou, Shoji Nishimura, Kanoksak Wattanachote, Timothy K. Shih, Neil Y. Yen

2013 IEEE 10TH INTERNATIONAL CONFERENCE ON AND 10TH INTERNATIONAL CONFERENCE ON AUTONOMIC AND TRUSTED COMPUTING (UIC/ATC) UBIQUITOUS INTELLIGENCE AND COMPUTING 308 - 313 2013年 [査読有り]

　概要を見る

Recently, eye-tracking has been widely applied in a wide spectrum of fields for both academic researches and Business. In this study, we concentrate on the analysis of instant (and often subconscious) information generated from interactions between an individual and devices, such as a PC, laptop, and mobile phone. We present the experiment design to capture and extract the viewing patterns in Twitter using the eye-tracking technology. We show a set of experiment results based on the analysis of eye gazing data, in order to demonstrate how the subjects look for specified keywords in the Twitter timeline, which can further contribute to categorization of viewing patterns.

DOI

Scopus

4

被引用数

(Scopus)
Organic Streams: Data Aggregation and Integration Based on Individual Needs

Xiaokang Zhou, Qun Jin, Bo Wu, Wei Wang, Julong Pan, Wenbin Zheng

2013 INTERNATIONAL JOINT CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY & UBI-MEDIA COMPUTING (ICAST-UMEDIA) 535 - + 2013年 [査読有り]

　概要を見る

With the high accessibility of the social media, more and more people have been accustomed to sharing their personal contents across the social networks, which results in an explosive increase of data scale. In this study, in order to support information and knowledge discovery in big data, we propose an approach to aggregation and integration of personal big data from life logs in accordance with individual needs, which can benefit the sustainable information utilization process. In details, the organic stream, which is designed as an extensible data carrier, is introduced and developed to formulize and organize the personal big data, in order to extract dynamical individual needs from the tremendous amount of data posted through social media, and further aggregate and integrate the related data in a meaningful way, which can also facilitate the personalized information retrieval and reuse process. The architecture of the system with the foundational modules is given, and the experiment result is presented to demonstrate the usability and effectiveness of our approach.

DOI

Scopus

3

被引用数

(Scopus)
Dynamically Identifying Roles in Social Media by Mapping Real World

Bo Wu, Qun Jin, Xiaokang Zhou, Wei Wang, Fuhua Lin, Henry Leung

2013 INTERNATIONAL JOINT CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY & UBI-MEDIA COMPUTING (ICAST-UMEDIA) 573 - + 2013年 [査読有り]

　概要を見る

With the rapid growing of users in the SNS environments, their network relationships in Internet have become as complex as in the real world. On the other hand, the user's social role plays an important role in providing individualized services, such as information recommendation in the SNS environments. However, as we know, people will switch or change their social roles dynamically in the real society, which is also true in the cyber network space, such as SNS. In this paper, we present a basic model to describe social roles in both the real world and the SNS environment, in which a set of attributes and factors are considered and introduced to represent the time-changing social roles in different situations and contexts. The mechanism that we develop to identify the roles is twofold: mapping of real world situations to cyber space, and analyzing social role attributes based on the mapping and synthesizing. We further describe an application scenario in regard to how to map the different situations and analyze the role attributes, in order to dynamically identify roles in the cyber space.

DOI

Scopus

4

被引用数

(Scopus)
Overview mobile social networking in proximity (MSNP): applications, characterstics and challenges

Yufeng Wang, Tang Jing, Qun Jin, Jianhua Ma

2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC) 2112 - 2119 2013年 [査読有り]

　概要を見る

Recently, mobile social networking applications have gained tremendous attention, which free users from face-to-monitor life, while they still can share information and stay in touch with their friends on the go. However most MSN applications regard mobile terminals just as entry points to existing social networks, depend on centralized servers (for storage and processing of all application/context data) and continual Internet connectivity, even though mobile users are within proximity area (like campus, event spot, and community), and can directly exchange data through various wireless technologies (e.g., WiFi Direct, etc.). In this paper, we focus on thoroughly overviewing the mobile social networking in proximity (MSNP), including existing applications, characteristics and challenges. Our primary goal is to identify the characteristics, technical challenges and potential solution for future MSNP applications, capable to flexibly adapt to different application domains and deployment requirements.

DOI

Scopus

7

被引用数

(Scopus)
Message from the FiSTA 2013 chairs

Jianhua Ma, Qun Jin, Rafael Santos, Agustinus Borgy Waluyo, Andrew Flahive, Bernady O. Apduhan, Atsuko Takefusa, Ching Hsien Hsu, Fenghui Yao, Guifeng Shao, Hai V. Tran, Hiroaki Higaki

Proceedings of the 2013 13th International Conference on Computational Science and Its Applications, ICCSA 2013 2013年 [招待有り]

DOI

Scopus
Special issue on cognitivebased text understanding and web wisdom

Xiangfeng Luo, Qing Li, Qun Jin, Feifei Xu

International Journal of Cognitive Informatics and Natural Intelligence 7 ( 2 ) 2013年 [招待有り]
Message from the ICWL 2013 program committee co-chairs

Yueh Min Huang, Frederick Li, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8167 LNCS 2013年 [招待有り]

担当区分：最終著者

DOI

Scopus
3^rd international workshop on advances in semantic information retrieval

Vitaly Klyuev, Maxim Mozgovoy, Stefano Borgo, Katarzyna Budzynska, Massimiliano Carrara, Jolanta Cybulka, Vladimir Dobrynin, Krzysztof Goczyla, Yannis Haralambous, Wladyslaw Homenda, Qun Jin, Janusz Kaczmarek, Tuomo Kakkonen, Piotr Kulicki, Cristian Lai, Sabina Leonelli, Simone Ludwig, Jacek Martinek, Nikolay Mirenkov, Ahsan Morshed, Grzegorz J. Nalepa, Raúl Palma, Maciej Piasecki, Evgeny Pyshkin, Marek Reformat, Roman Shtykh, Larisa Soldatova, Mari Carmen Suárez De Figueroa Baonza, T. Tadeusiewicz, Robert Trypuz, Miroslav Vacura, Eloisa Vargiu, Alexander Vazhenin, Haofen Wang, Shih Hung Wu, Slawomir Zadrozny, Agnieszka Lawrynowicz

2013 Federated Conference on Computer Science and Information Systems, FedCSIS 2013 241 2013年 [招待有り]
Special issue on technology-enhanced social learning

Chengjiu Yin, Xinyou Zhao, Qun Jin

International Journal of Distance Education Technologies 11 ( 1 ) 2013年01月 [招待有り]

担当区分：最終著者
Integration of range-based and range-free localization algorithms in wireless sensor networks for mobile clouds

Yufeng Wang, Qun Jin, Jianhua Ma

Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013 957 - 961 2013年 [査読有り]

　概要を見る

Usually, in mobile server cloud computing (MSCC) environments, there exist enormous sensors conducting various tasks. Localization of sensor nodes using the technologies in Wireless Sensor Network (WSN) is critical to both cloud infrastructure operations and most applications. Specifically, in WSN, Malguki (the method's name, Malguki, means 'spring') is an effective range-based algorithm which can compute the location of a node using noisy distance estimations. However, through simulation, we found that, in original Malguki algorithm that uses an iterative process to locate unknown nodes, the initial positions of unknown nodes in iteration are evenly and randomly selected, which may cause large average localization error. Considering the mentioned weak point, this paper proposes to enhance the Malguki with a simple range-free Centroid localization algorithm, which intentionally obtains initial positions of unknown nodes in iteration by Centroid algorithm. Simulation results show that the integration of range-based and range-free localization algorithm, Centroid Malguki always performs better than original Malguki algorithm. © 2013 IEEE.

DOI

Scopus

18

被引用数

(Scopus)
Erratum: Effective session key distribution for secure fast handover in mobile networks (Telecommunication Systems (DOI 10.1007/s11235-009-9219-0))

Jong Hyuk Park, Qun Jin

Telecommunication Systems 52 ( 1 ) 359 2013年01月 [査読有り]

担当区分：最終著者

DOI

Scopus
An adaptively emerging mechanism for context-aware service selections regulated by feedback distributions

Yishui Zhu, Qun Jin

Human-centric Computing and Information Sciences 2 ( 1 ) 1 - 15 2012年12月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

15

被引用数

(Scopus)
Special Issue on Multidisciplinary Emerging Networks and Systems Foreword

Qun Jin, Yufeng Wang

JOURNAL OF COMPUTER AND SYSTEM SCIENCES 78 ( 6 ) 1671 - 1672 2012年11月 [招待有り]

担当区分：筆頭著者

DOI

Scopus
Socialized ubiquitous personal study: Toward an individualized information portal

Hong Chen, Xiaokang Zhou, Qun Jin

JOURNAL OF COMPUTER AND SYSTEM SCIENCES 78 ( 6 ) 1775 - 1792 2012年11月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

10

被引用数

(Scopus)
Organic Stream: Meaningfully Organized Social Stream for Individualized Information Seeking and Knowledge Mining

X. Zhou, J. Chen, Q. Jin, T.K. Shih

Proc. U-Media2012 (The 5th IET International Conference on Ubi- Media Computing) 2012年08月 [査読有り]
Goal-Driven Process Navigation for Individualized Learning Activities in Ubiquitous Networking and IoT Environments

Jian Chen, Qun Jin, Runhe Huang

JOURNAL OF UNIVERSAL COMPUTER SCIENCE 18 ( 9 ) 1132 - 1151 2012年 [査読有り]

担当区分：責任著者
AB-Chord: an efficient approach for resource location in structured P2P networks

Yufeng Wang, Xiangming Li, Qun Jin, Jianhua Ma

2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INTELLIGENCE & COMPUTING AND 9TH INTERNATIONAL CONFERENCE ON AUTONOMIC & TRUSTED COMPUTING (UIC/ATC) 278 - 284 2012年 [査読有り]

　概要を見る

Recently, P2P (Peer-to-Peer) technology has witnessed a rapid development. Basically, one of key components in successful P2P applications is how to efficiently look up resources. Considering that structured P2P is a relatively efficient way to locate resources, this paper conducted two improvements to increase the search efficiency in Chord-based algorithms, one of the most popular structured P2P resource lookup protocols. In detail, our contributions are twofold. First, considering the fact that routing information in Chord is not abundant enough for efficient resource search, and looking up resource can only be enforced in clockwise direction, a new algorithm called AB-Chord is proposed to reconstruct the finger tables in Chord, in which counter-clockwise finger table is added to achieve resource queries in both directions, and the density of neighboring fingers is increased. Additionally, AB-Chord implements a new operation to remove the redundant fingers introduced by adding fingers in AB-Chord. Experimental results show that AB-Chord's query efficiency has been improved in terms of the average lookup hops and average lookup delay. And furthermore, considering that the proposed AB-Chord algorithm enlarged the finger table which may cause the forwarding-storm of routing maintenance messages, we further propose AB-Chord+, which appropriately extends the periodic time of updating finger tables and makes the joining and leaving nodes actively send updating messages, to reduce the number of messages forwarded in the network. Simulated results show that AB-Chord+ reduced the network bandwidth consumption.

DOI

Scopus

8

被引用数

(Scopus)
Attachment factor in user experience over a time span: Experiment design and analysis

Shinichiro Kajiwara, Qun Jin

ACM International Conference Proceeding Series 45 - 50 2012年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012: Preface

Xiaohong Jiang, Qun Jin, Hong Liu, Shaozi Li

Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012 2 2012年 [査読有り] [招待有り]

DOI

Scopus
Welcome message from the HumanCom 2012 general chairs

Qun Jin, Martin Sang Soo Yeo, Bin Hu

Lecture Notes in Electrical Engineering 182 LNEE 2012年 [招待有り]

担当区分：筆頭著者
User-centric integrated recommendation by gradual adaptation based on focus of interests and its transition

Jian Chen, Xiaokang Zhou, Qun Jin

Proceedings - 2012 IEEE 12th International Conference on Computer and Information Technology, CIT 2012 435 - 441 2012年 [査読有り]

担当区分：最終著者

DOI

Scopus
Message from MENS-12 symposium chairs

Yoshiaki Kakuda, Yufeng Wang, Jianhua Ma, Qun Jin, Zhingming Cai, Chin-Chih Chang, Yinong Chen, Felicita Di Giandomenico, Juergen Dunkel, Xinxin Fan, Cheng Fu, Ruijun He, Teresa Higuera, Eitaro Kohno, Runhe Huang, Ruidong Li, Miroslaw Malek, Tomoyuki Ohta, Yizhi Ren, Achim Rettberg, Kenichi Takahashi, Athanasios V. Vasilakos, Feng Xia, Baoliu Ye, Deqing Zou

Proceedings - IEEE 9th International Conference on Ubiquitous Intelligence and Computing and IEEE 9th International Conference on Autonomic and Trusted Computing, UIC-ATC 2012 xl - xli 2012年 [招待有り]

DOI

Scopus
On studying relationship between altruism and the psychological phenomenon of self-deception in rational and autonomous networks

Yufeng Wang, Athanasios V. Vasilakos, Qun Jin, Jianhua Ma

Proceedings - 32nd IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2012 336 - 341 2012年 [査読有り]

　概要を見る

In open networking environments, resources, services, strategies and actions are voluntarily provided, maintained, chosen and determined by independent, rational and autonomous peers. Basically, Game theory is a basic tool for modeling choices by rational agents in those environments, which, usually assumes players choose strategies which maximize utility of game outcomes given their beliefs about what others players will do. This means that the most challenging question is often how beliefs are formed. Intuitively, beliefs depend not only on what people know to be true, but also on what they want to be true (desire). This paper introduces a model of rational choices that allows for this possibility that peers' beliefs are affected by their interests (desires), and, based on this model, analyzes the impact of psychological belief (optimistic bias and pessimistic bias) on the existing altruism-based cooperative mechanisms in Peer-to-Peer (P2P) systems. We found that, when there exist free riders, on the contrary to the intuitive thought, pessimistic bias of belief on contribution level can facilitate the P2P systems to converge to the stable equilibrium in easier way than optimistic bias. © 2012 IEEE.

DOI

Scopus

8

被引用数

(Scopus)
Message from the Third International Workshop on Future Information System Technologies and Applications (FISTA 2012) chairs

Bernady O. Apduhan, Jianhua Ma, Qun Jin

Proceedings - 12th International Conference on Computational Science and Its Applications, ICCSA 2012 xxix 2012年 [招待有り]

担当区分：最終著者

DOI

Scopus
Knowledge organization aided by eye-tracking in a social media enhanced learning environment

Xiaokang Zhou, Guangyu Piao, Qun Jin

Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012 1 6 - 10 2012年 [査読有り]

担当区分：最終著者

DOI

Scopus
User correlation discovery and dynamical profiling based on social streams

Xiaokang Zhou, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7669 53 - 62 2012年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

9

被引用数

(Scopus)
Learning activity sharing and individualized recommendation based on dynamical correlation discovery

Xiaokang Zhou, Jian Chen, Qun Jin, Timothy K. Shih

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7558 200 - 206 2012年 [査読有り]

担当区分：責任著者

DOI

Scopus
A human-centric integrated approach to web information search and sharing

Roman Y Shtykh, Qun Jin

Human-centric Computing and Information Sciences 1 ( 1 ) 1 - 37 2011年12月 [査読有り]

担当区分：最終著者

DOI

Scopus

49

被引用数

(Scopus)
Pervasive Learning Tools and Technologies

Neil Y. Yen, Qun Jin, Hiroaki Ogata, Timothy K. Shih, Y. Yano

Pervasive Computing and Networking 37 - 50 2011年06月 [査読有り]

DOI

Scopus

2

被引用数

(Scopus)
Message from the CPSCom 2011 workshop chairs

Qun Jin, Alvin Chin, Yan Zhang

Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011 28 2011年 [招待有り]

担当区分：筆頭著者

DOI

Scopus
A multiple response approach for adaptive learning service with context-based multimedia contents

Xinyou Zhao, Qun Jin, Toshio Okamoto

Lecture Notes in Electrical Engineering 102 LNEE 269 - 280 2011年 [査読有り]

DOI

Scopus
Constructing robust digital identity infrastructure for future networked society

Jianming Yong, Sanjib Tiwari, Xiaodi Huang, Qun Jin

Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2011 570 - 576 2011年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
A service-oriented architecture for context-aware ubiquitous learning delivery

Xinyou Zhao, Qun Jin

Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 4 2461 - 2465 2011年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Foreword

Qun Jin

Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures 2011年 [招待有り]

担当区分：筆頭著者

DOI

Scopus
CAPK: A learning process model for web 2.0 technology enhanced community of practice

Haifeng Man, Hong Chen, Yan Wu, Qun Jin

Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011 546 - 551 2011年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
A hybrid P2P search engine for social learning

Ashraf Uddin Ahmed, Tanvir Shahid, Hong Chen, Qun Jin

Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011 564 - 569 2011年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Goal-driven navigation for learning activities based on process optimization

Jian Chen, Haifeng Man, Qun Jin, Runhe Huang

Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011 389 - 395 2011年 [査読有り]

　概要を見る

This paper describes an integrated approach to provide an optimized learning process to students by analyzing the log data of learning activities and extracting their learning patterns. Our analysis results show that most of students almost always use their main learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimize the process of learning actions using the extracted learning patterns, infer the learning goal of students, and then navigate them a personalized learning process according to the similarity of the extracted learning patterns. © 2011 IEEE.

DOI

Scopus

2

被引用数

(Scopus)
Enabling open learning process with learning activity streams: Model, metaphor and specification

Haifeng Man, Hong Chen, Jian Chen, Xiaokang Zhou, Yan Wu, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7048 233 - 242 2011年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

1

被引用数

(Scopus)
Automated lecture template generation in CORDRA-based learning object repository

Neil Y. Yen, Timothy K. Shih, Qun Jin, Li-Chieh Lin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7048 295 - 304 2011年 [査読有り]

　概要を見る

Sharing resources and information on Internet has become an important activity for education. The MINE Registry, a branch of distributed repository, inherited the architecture of CORDRA has been developed for storing and sharing Learning Objects. Following the usage experiences, especially those being utilized to generate the lecture, the interaction structure is defined to clarify the relationships among Learning Objects. The methods to social network analysis are applied to quantify the implicit correlations and to evaluate the interdependency. In addition, an intelligent mining algorithm is proposed to explore the developed interaction structure and automatically generates lecture templates corresponding to the query criteria. The concentration of this study is to facilitate the complex and time-consuming process of creating lectures through a simple search mechanism. The implemented system has demonstrated the preliminary results and the feasibility are also revealed by the evaluation results. © 2011 Springer-Verlag.

DOI

Scopus
Automatic learning sequence template generation for educational reuse

Neil Y. Yen, Qun Jin, Timothy K. Shih, Li-Chieh Lin

Proceedings - 2011 IEEE International Conference on Granular Computing, GrC 2011 773 - 778 2011年 [査読有り]

　概要を見る

Sharing resources and information on Internet has become an important activity for education. The learning object repository has been developed to achieve efficient management of learning objects. Following usage experiences of learning objects collected in the past, this study concentrates on investigating implicit information between learning objects. We define a social structure for identifying relationship between learning objects and define a set of metrics to evaluate the interdependency. The structure identifies usage experiences and can be graphed in terms of implicit and explicit relations among learning objects. As a practical contribution, an adaptive algorithm is proposed to mine the social structure. The algorithm generates adaptive learning sequence by identifying possible interactive search input and assists them in completing self-paced learning situation. © 2011 IEEE.

DOI

Scopus

1

被引用数

(Scopus)
Discovery of implicit correlation between shared information in an open environment

Neil Y. Yen, Qun Jin

MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - ACM International Workshop on Multimedia Technologies for Distance Learning, MTDL'11 43 - 46 2011年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Flowable services: A human-centric framework toward service assurance

Qun Jin, Yishui Zhu, Roman Y. Shtykh, Neil Y. Yen, Timothy K. Shih

Proceedings - 2011 10th International Symposium on Autonomous Decentralized Systems, ISADS 2011 653 - 658 2011年 [査読有り]

　概要を見る

Service computing aims to provide IT and computing resources to users in a way that it simply serves them. However, many issues remain in, such as portability, interoperability, and heterogeneity of diverse services, in addition to service modeling, creation, deployment, discovery, recommendation, composition, and delivery, in order to provide a service that best fits user needs and contexts at the time. In this study, we propose a new model of flowable services. Its primary purpose is to realize seamless integration and provision of diverse services in an intuitive "flowable" way maximally close to the "flow" of users' activities and thoughts, and as pertinent as possible to their needs, thus gain the most satisfaction. In this paper, we propose and discuss a human-centric framework of flowable services toward service assurance. We further describe the evaluation of the model, and an application scenario for adaptive delivery of personalized learning service under the proposed framework.

DOI

Scopus

2

被引用数

(Scopus)
Adaptive object re-ranking mechanism for ubiquitous learning environment

Neil Y. Yen, Timothy K. Shih, Qun Jin, Jason C. Hung, Qingguo Zhou, Louis R. Chao

Journal of Multimedia 6 ( 2 ) 129 - 138 2011年 [査読有り]

　概要を見る

Ubiquitous Learning (U-Learning), as an emerging learning paradigm, makes it possible for learners to carry out the learning activities at any places and at anytime. With the advantages of the devices, learners can obtain a variety of supplementary materials from the Internet. In the scope of distance learning, LOR (Learning Object Repository) stands for managing and sharing of learning related materials (known as learning objects). However, some challenges may raise while performing these activities. For instance, a huge amount of learning objects may appear while learners utilize the search service provided by LOR. Learners have to spend time on collecting relevant resources for specific purposes. This situation may discourage the reusability of learning objects especially in a ubiquitous environment. In this paper, based on systematic re-examination of reuse scenarios, an adaptive mechanism, as a resource discovery and search middleware, was proposed to assist learners in obtaining possible objects under ubiquitous environment. Achievement of the proposed mechanism can produce search results adaptive to specific situations in order of similarity degree based on the mixed information. We try to filter out some irrelevant results by using the past usage history, current geographical information and input query, so as to enhance the efficiency of learning objects retrieval in a ubiquitous environment. As a pilot test, Apple iPhone was utilized to be the major client testbed. © 2011 Academy Publisher.

DOI

Scopus

7

被引用数

(Scopus)
Generating associative ripples of relevant information from a variety of data streams by throwing a heuristic stone

Xiaokang Zhou, Hong Chen, Qun Jin, Jianming Yong

Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2011 2011年 [査読有り]

　概要を見る

Recently, the vast dialog in the microblog, such as twitter, Facebook has become increasingly popular. As we post more messages in microblogs, information is spreading more quickly and widely. These widely spread and diversified contents could be viewed as data streams, which have become an important part of the Internet resources. However, these separated data streams are littery and meaningless, so we need to collect and organize them together to provide us with meaningful information. It is hard to imagine that we could find useful information by simply inputting a few keywords into a search engine in such a stream environment. In this study, we try to find a way to seek the information related to users' personal and current interests and needs among these data streams and provide users with other more relevant information. We introduce a set of metaphors to represent a variety of data streams in different levels, and define two new metaphors: heuristic stone and associative ripple to assist the seeking process and describe the results. Based on these, we further propose two algorithms for the information seeking and processing, and discuss a scenario of the information seeking process that utilizes the proposed metaphors and algorithms. Copyright 2011 ACM.

DOI

Scopus
Dynamical user networking and profiling based on activity streams for enhanced social learning

Xiaokang Zhou, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7048 219 - 225 2011年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

8

被引用数

(Scopus)
Organizing learning stream data by eye-tracking in a blended learning environment integrated with social media

Xiaokang Zhou, Guangyu Piao, Qun Jin, Runhe Huang

ITME 2011 - Proceedings: 2011 IEEE International Symposium on IT in Medicine and Education 2 335 - 339 2011年 [査読有り]

　概要を見る

In this study, we integrate social media into the blended learning environment, and further delve into utilizing the eye-tracking technology to enhance learning to be socialized and more efficient. We propose an approach to employ eye-tracking to extract those related learning stream data according to different seeking patterns in a learning process. Based on these, we go further to organize these raw stream data into meaningful learning contents in accordance with specific tasks in order to benefit both teachers and students, which can assist the learning process and promote the learning efficiency in the blended learning environment. © 2011 IEEE.

DOI

Scopus

5

被引用数

(Scopus)
Effective session key distribution for secure fast handover in mobile networks

Jong Hyuk Park, Qun Jin

TELECOMMUNICATION SYSTEMS 44 ( 1-2 ) 97 - 107 2010年06月 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Evaluation of Drowsiness during Driving based on Heart Rate Analysis - a driving simulation study

Masaru Tasaki, Hui Wang, Motoaki Sakai, Mai Watanabe, Qun Jin, Daming Wei

2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW) 411 - 416 2010年 [査読有り]

　概要を見る

t is a common sense that drowsiness during driving could cause traffic accidents. Related researches show that drowsiness occurs when the parasympathetic nerve system predominates over others, and the high frequency (HF) component of heart rate variability (HRV) on an electrocardiogram (ECG) is closely related with the parasympathetic nerve activity, so it is reasonable to evaluate drowsiness based on heart rate analysis. In the driving simulation study, ECG and calculated R-R intervals were put on record during the monitoring process of drowsiness degrees. Relations among different indexes, such as, temporal change of HF band, RR50, Coefficient of Variation of R-R interval (CVRR), and LF to HF ratio (LF/HF) were evaluated as well. The experimental results suggest that there exist certain correlations between drowsiness and HF, RR50, CVRR, or LF/HF, which will be compared in the future with data collected in real driving experiments.

DOI

Scopus

2

被引用数

(Scopus)
Dynamic Navigation for Personalized Learning Activities Based on Gradual Adaption Recommendation Model

Jian Chen, Haifeng Man, Neil Y. Yen, Qun Jin, Timothy K. Shih

ADVANCES IN WEB-BASED LEARNING-ICWL 2010 6483 31 - + 2010年 [査読有り]

　概要を見る

This study aims to provide learners with appropriate learning activities navigation based on a learning process recommendation system that gradually adapts to their needs. A learning activity consists of a series of purposeful learning actions with a specific sequence. In the system, user profile is generated from various learning related activities that are collected over different time spans. A dynamic user group is generated based on the similarity of user profiles which have had successful learning experience, and can be used to create a personalized navigation of learning activities for a target learner. In this paper, after introducing how to create a dynamic design of learning activities navigation, we focus on discussing the design and implementation issues of the prototype system for personalized learning support.

DOI

Scopus

8

被引用数

(Scopus)
Open Learning: A Framework for Sharable Learning Activities

Haifeng Man, Hong Chen, Qun Jin

ADVANCES IN WEB-BASED LEARNING-ICWL 2010 6483 387 - 392 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
A novel WYSIWYG approach for generating cross-Browser web data

Jin Zhu, Xiao Liu, Yoshiyori Urano, Qun Jin

Proceedings - 2010 10th International Conference on Computational Science and Its Applications, ICCSA 2010 155 - 164 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Shift to Cyber-I: Reexamining personalized pervasive learning

Neil Y. Yen, Qun Jin, Jianhua Ma, Runhe Huang, Timothy K. Shih

Proceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010 685 - 690 2010年 [査読有り]

　概要を見る

Recently, there have been lots of researches on how to provide personalized services to different users according to their personal characters, needs, situations, contexts and so on. Such personalized services are often based on users' profiles provided by the users in the beginning, and users' records or experiences in using corresponding systems in certain periods. However, different systems or terminals collect user information independently and cannot share the user's personal information collected by these different systems/terminals. As a result, each system can only utilize the limited information collected by the system itself to provide services or recommendations, and it thus cannot meet what users' needs in varied situations across the different systems/terminals. Therefore, it is still an open issue on how to gather, share and utilize various kinds of personal information to effective personalized services in right time, right place and right means to users. In this paper, a case study for personalized pervasive learning is discussed as one typical application of the concept of Cyber-I, an individual's counterpart on the cyberspace. The Cyber-I aims to provide a better environment for users to obtain what they may really need on the Web, and it can be considered as an innovated possibility of web usage scenario in the near future. Our case study using pervasive devices (iPad, cell phone, and laptop) for learning issues can be regarded as the best practice to support the proposed Cyber-I. © 2010 IEEE.

DOI

Scopus

6

被引用数

(Scopus)
A framework of organic streams: Integrating dynamically diversified contents into ubiquitous personal study

Hong Chen, Xiaokang Zhou, Haifeng Man, Yan Wu, Ashraf Uddin Ahmed, Qun Jin

Proceedings - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC 2010 and ATC 2010 Conferences, UIC-ATC 2010 386 - 391 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

7

被引用数

(Scopus)
Preface of MENS'10: The 2nd International Symposium on Multidisciplinary Emerging Networks and Systems

Yufeng Wang, Goutam Chakraborty, Kuan-Ching Li, Tadashi Dohi, Mieso Denko, Ma. Jianhua, Qun Jin

Proceedings - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC 2010 and ATC 2010 Conferences, UIC-ATC 2010 xxxv - xxxvi 2010年 [招待有り]

担当区分：最終著者

DOI

Scopus
A new paradigm of ranking & searching in learning object repository

Neil Y. Yen, Timothy K. Shih, Qun Jin

MTDL'10 - Proceedings of the 2010 ACM Workshop on Multimedia Technologies for Distance Leaning, Co-located with ACM Multimedia 2010 1 - 6 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
Harnessing user contexts to enable flowable services model

Yishui Zhu, Roman Y. Shtykh, Qun Jin

2010 3rd International Conference on Human-Centric Computing, HumanCom 2010 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
A re-examination of ranking metrics for Learning Object repository

Neil Y. Yen, Ying-Hong Wang, Qun Jin, David J.T. Yang

2010 3rd IEEE International Conference on Ubi-Media Computing, U-Media 2010 91 - 94 2010年 [査読有り]

　概要を見る

In line with the popularity of Internet and the development of search engine, users request information through Web-based services. Although general purpose searching such as one provided by Google is powerful, searching mechanism for specific purposes could rely on metadata. We followed SCORM and CORDRA specifications to develop a registry system, called the MINE Registry, for storing and sharing 20,738 Learning Objects created in the past five years. As a contribution, we propose the concept of "Reusability Tree" to represent the relationships among relevant Learning Objects and to enhance CORDRA. We further collect relevant information while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from community users are also considered as critical elements for evaluating significance degree of Learning Objects. Through these factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories. © 2010 IEEE.

DOI

Scopus
Provision of flowable services in cloud computing environments

Yishui Zhu, Roman Y. Shtykh, Qun Jin

2010 5th International Conference on Future Information Technology, FutureTech 2010 - Proceedings 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
An agent based approach for promoting interactive teaching and active learning

Runhe Huang, Jianhua Ma, Qun Jin

2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010 349 - 354 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
An integrated system to assist personalized learning based on gradual adaption recommendation model

Jian Chen, Qun Jin, Jianhua Ma, Runhe Huang

2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010 300 - 306 2010年 [査読有り]

　概要を見る

This study presents an integrated adaptive system to support and facilitate individual learning based on a recommendation model that gradually adapts to a learner's needs and information access behaviors, including various learning related activities, over different time spans. In this paper, we focus on describing the integrated framework and discussing the design and implementation issues of the prototype system for personalized learning support. ©2010 IEEE.

DOI

Scopus

1

被引用数

(Scopus)
Putting adaptive granularity and rich context into learning objects

Haifeng Man, Qun Jin

2010 9th International Conference on Information Technology Based Higher Education and Training, ITHET 2010 140 - 145 2010年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Trend of e-learning: The service mashup

Neil Y. Yen, Timothy K. Shih, Qun Jin, Hui-Huang Hsu, Louis R. Chao

International Journal of Distance Education Technologies 8 ( 1 ) 69 - 88 2010年01月 [査読有り]

　概要を見る

With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack interoperability. The only way to reuse these applications is to redevelop them for specific purposes. In order to solve this situation and norm the various learning resources, IMS proposes a new e-learning standard named "Common Cartridge". This standard not only integrates the past e-learning standards like LOM, SCORM and QTI but also proposes a technical architecture called Learning Tools Interoperability to allow applications to reuse different systems without reprogramming. In this paper, we firstly introduce the current e-learning environment. Then we pay attention on the usage of Common Cartridge standards and discuss the architecture of Learning Tools Interoperability. According to these standards, we will point out the e-learning standard that might be widely utilized in the future. Copyright © 2010, IGI Global.

DOI

Scopus

1

被引用数

(Scopus)
Ubiquitous Personal Study: a framework for supporting information access and sharing

Hong Chen, Qun Jin

PERSONAL AND UBIQUITOUS COMPUTING 13 ( 7 ) 539 - 548 2009年10月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

16

被引用数

(Scopus)
Specification, standards and information management for distributed systems

Irfan Awan, Qun Jin, Kuo-Ming Chao

COMPUTER STANDARDS & INTERFACES 31 ( 5 ) 869 - 869 2009年09月 [招待有り]

DOI

Scopus
Dynamically constructing user profiles with similarity-based online incremental clustering

Roman Y. Shtykh, Qun Jin

International Journal of Advanced Intelligence Paradigms 1 ( 4 ) 377 - 397 2009年06月 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

7

被引用数

(Scopus)
Integrating Search and Sharing: User-Centric Collaborative Information Seeking

Roman Y. Shtykh, Qun Jin

PROCEEDINGS OF THE 8TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE 388 - + 2009年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Resource Retrieval Service to Enhance U-Learning Environment

Neil Y. Yen, Louis R. Chao, Qun Jin, Jianhua Ma, Timothy K. Shih

PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INFORMATION TECHNOLOGIES & APPLICATIONS (ICUT 2009) 365 - + 2009年 [査読有り]

　概要を見る

E-Learning makes it possible for learners to study at any time. With the improvement of ubiquitous technologies and corresponding devices, learners can conduct their learning activities without any limitations from the environment. Instructors can utilize various kinds of resources to create more plentiful learning materials for learners. In this situation, instructors or learners have to spend more time on collecting relevant resources for a specific purpose. In our previous works, we utilized the geographical information and RFID (Radio Frequency Identification) to develop an outdoor adventure game to support learning procedures. In this paper, we go further to propose and develop a resource retrieval mechanism to assist learners in collecting relevant learning resources. This mechanism can be regarded as a search procedure. We aim at providing search results in the order of relevant degree based on learners' current geographical information. It can make resource retrieval more efficient in ubiquitous learning environments.

DOI

Scopus
A Context-Aware Framework for Flowable Services

Roman Y. Shtykh, Yishui Zhu, Qun Jin

THIRD INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING (MUE 2009) 251 - + 2009年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Preface of MANS'09

Yufeng Wang, Kuan Ching Li, Qun Jin, Hongbo Zhu, Jianhua Ma

UIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences 2009年 [招待有り]

DOI

Scopus
A flowable service model for seamless integration of services

Yishui Zhu, Roman Y. Shtykh, Qun Jin, Jianhua Ma

Proceedings of the IASTED International Conference on Advances in Computer Science and Engineering, ACSE 2009 199 - 204 2009年 [査読有り]
Information sharing across diverse media platforms with reconfigurable user grouping

Roman Y. Shtykh, Qun Jin, Guozhen Zhang, Runhe Huang

Proceedings of the IASTED International Conference on Advances in Computer Science and Engineering, ACSE 2009 89 - 94 2009年 [査読有り]
Message from the 2CCom 2009 symposium chairs

Albert Zomaya, Qun Jin, Bharat K. Bhargava, Naixue Xiong, Sang Soo Yeo

Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 2 2009年 [招待有り]

DOI

Scopus
Message from the PICom-09 chairs

William Zhu, Qun Jin, Alessio Vecchio, Mingtian Zhou, Ajith Abraham, Hussein Mouftah, Jianhua Ma, Laurence T. Yang

8th IEEE International Symposium on Dependable, Autonomic and Secure Computing, DASC 2009 xxi - xxii 2009年 [招待有り]

DOI

Scopus
A web recommender system based on dynamic sampling of user information access behaviors

Jian Chen, Roman Y. Shtykh, Qun Jin

Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009 2 172 - 177 2009年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
A user location-aware music playing system

Youhei Katori, Jianhua Ma, Tomomi Kawashima, Bernady O. Apduhan, Runhe Huang, Qun Jin

UIC-ATC 2009 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing in Conjunction with the UIC'09 and ATC'09 Conferences 377 - 382 2009年 [査読有り]

担当区分：最終著者

DOI

Scopus
A tree-structured intelligence entity pool and its sharing among ubiquitous objects

Runhe Huang, Jianhua Ma, Qun Jin

Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 2 318 - 325 2009年 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
Improving Mobile Web Search Experience with Slide-Film Interface

Roman Y. Shtykh, Qun Jin

SITIS 2008: 4TH INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGY AND INTERNET BASED SYSTEMS, PROCEEDINGS 659 - + 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Inferring User Interests from Relevance Feedback with High Similarity Sequence Data-Driven Clustering

Roman Y. Shtykh, Qun Jin

PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON UNIVERSAL COMMUNICATION 390 - + 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Harnessing user contributions and dynamic profiling to better satisfy individual information search needs

Roman Y. Shtykh, Qun Jin

INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES 4 ( 1 ) 63 - 79 2008年 [査読有り]

担当区分：最終著者, 責任著者

DOI

Scopus

6

被引用数

(Scopus)
Implementation of Ubiquitous Personal Study Using Web 2.0 Mash-up and OSS Technologies

Hong Chen, Nozomi Ikeuchi, Qun Jin

2008 22ND INTERNATIONAL WORKSHOPS ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOLS 1-3 1573 - 1578 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

9

被引用数

(Scopus)
Slide-film interface: Overcoming small screen limitations in mobile web search

Roman Y. Shtykh, Jian Chen, Qun Jin

ADVANCES IN INFORMATION RETRIEVAL 4956 622 - + 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Robots in smart spaces - A case study of a u-object finder prototype

Tomomi Kawashima, Jianhua Ma, Bernady O. Apduhan, Runhe Huang, Qun Jin

UBIQUITOUS INTELLIGENCE AND COMPUTING, PROCEEDINGS 5061 61 - + 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

5

被引用数

(Scopus)
Modeling and analyzing individual's daily activities using lifelog

Katsuhiro Takata, Jianhua Ma, Bernady O. Apduhan, Runhe Huang, Qun Jin

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS 503 - + 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

16

被引用数

(Scopus)
Message from the UASS 2008 chairs

Jong Hyuk Park, Laurence T. Yang, Jianhua Ma, Qun Jin, Hangbae Chang

Proceedings - International Conference on Advanced Information Networking and Applications, AINA 73 2008年 [招待有り]

DOI

Scopus
IMIS 2008 message from the workshop organizers MUE 2008

Seong Moo Yoo, Bonam Kim, Hui Huang Hsu, Ilsun You, Jong Hyuk Park, Minyi Guo, Ching Hsien Hsu, David Simplot-Ryl, Edwin H.M. Sha, Hai Jin, Javier Lopez, Shu Ching Chen, Tatsuya Yamazaki, Junmo Yang, Wen Tzeng Huang, Akiyo Nadamoto, Chengcui Zhang, Ching Sheng Wang, Chunming Rong, Frode Eika Sandnes, Geyong Min, Howard Leung, Hyobeom Ahn, Hyunju Kim, Indrakshi Ray, Isabelle Simplot-Ryl, Ismail Khalil Ibrahim, Javier García-Villalba, Jemal H. Abawajy, Jinhua Guo, Jon Youn, Kouichi Sakurai, Kuei Ping Shih, Lawrence Y. Deng, Mei Ling Shyu, Mohammad Al-Shurman, Oh Heum Kwon, Pedro M. Ruiz, Pilar Herrero, Q. Shi, Qun Jin, Seungjin Park, Sang Hyuk Son, Whai En Chen, Witold Pedrycz, Xiaofeng Chen, Yin Fu Huang

Proceedings - 2008 International Conference on Multimedia and Ubiquitous Engineering, MUE 2008 2008年 [招待有り]

DOI

Scopus
Capturing user contexts: Dynamic profiling for information seeking tasks

Roman Y. Shtykh, Qun Jin

Proc. - The 3rd Int. Conf. Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: Int. Conf. Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services 365 - 370 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

15

被引用数

(Scopus)
Proceedings - 2008 IEEE Congress on Services, SERVICES 2008: Message from SCCM 2008 Chairs

Mika Ylianttila, Jin Qun, Minyi Guo, Heming Zhang, Zhixiong Chen, Jukka Riekki, Jiehan Zhou, Mika Rautiainen

Proceedings - 2008 IEEE Congress on Services, SERVICES 2008 PART2 2008年 [招待有り]

DOI

Scopus
Gradual adaption model for estimation of user information access behavior

Jian Chen, Roman Y. Shtykh, Qun Jin

Proc. - The 3rd Int. Conf. Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: Int. Conf. Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services 378 - 383 2008年 [査読有り]

担当区分：最終著者

DOI

Scopus

2

被引用数

(Scopus)
Enhancing IR with user-centric integrated approach of interest change driven layered profiling and user contributions

Roman Y. Shtykh, Qun Jin

Proceedings - 21st International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINAW'07 2 240 - 245 2007年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Ubisafe computing: Vision and challenges (I)

Jianhua Ma, Qiangfu Zhao, Vipin Chaudhary, Jingde Cheng, Laurence T. Yang, Runhe Huang, Qun Jin

AUTONOMIC AND TRUSTED COMPUTING, PROCEEDINGS 4158 386 - 397 2006年 [査読有り]

担当区分：最終著者
Scalable information sharing utilizing decentralized P2P networking integrated with centralized personal and group media tools

Guozhen Zhang, Qun Jin

20TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 2, PROCEEDINGS 2 707 - + 2006年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Enhancing ontology-based context modeling with temporal vector space for ubiquitous intelligence

Shermann S. M. Chan, Qun Jin

20TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 1, PROCEEDINGS 1 669 - + 2006年 [査読有り]

担当区分：最終著者

DOI

Scopus
Collaboratively shared information retrieval model for e-learning

Shermann S. M. Chan, Qun Jin

ADVANCES IN WEB BASED LEARNING - ICWL 2006 4181 123 - 133 2006年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Message from CAUL 2006 Workshop Organizers

Shian Shyong Tseng, Kinshuk, Stephen J.H. Yang, Gwo Jen Hwang, Nian Shing Chen, Mohamed Ally, Johnny Biström, Jan Brase, William C.C. Chu, Jen Yao Chung, Francis C.M. Lau, Kuo En Chang, Gwo Dong Chen, Ming Syan Chen, Irene Chen, Shih Wei Chou, Andrea Detti, Claus Eikemeier, Jun H. Jo, Yueh Min Huang, Qun Jin, Vicki Jones, Soraya Kouadri Most'efaoui, Jaakko Kurhila, Stefano Levialdi, Sheng Tun Li, Anthony Y.H. Liao, Pierpaolo Loreti, Kiyoshi Nakabayashi, Haruo Nishinosono, Caoimhín O'Nualláin, Timothy K. Shih, Charles A. Shoniregun, Marten J. Van Sinderen, Judy C.R. Tseng, David Yang, Yao Ming Yeh, Pao Ta Yu, Jia Zhang, Rick Chen, Angus Huang, Jeff Huang, Blue Lan, Norman Shao, Addison Su, Jun Ming Su, Jui Feng Weng

Proceedings - IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing 2006 I 2006年 [招待有り]

DOI

Scopus
A survey of distance education challenges and technologies

Timothy K. Shih, Jason C. Hung, Jianhua Ma, Qun Jin

Future Directions in Distance Learning and Communication Technologies 1 ( 1 ) 1 - 25 2006年 [査読有り]

担当区分：最終著者

DOI

Scopus

6

被引用数

(Scopus)
Design of bookmark-based information space to support exploration and rediscovery

Roman Y. Shtykh, Jin Qun

Proceedings - Sixth IEEE International Conference on Computer and Information Technology, CIT 2006 2006年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Peer-to-peer solution to support group collaboration and information sharing

Roman Shtykh, Guozhen Zhang, Qun Jin

International Journal of Pervasive Computing and Communications 1 ( 3 ) 187 - 198 2005年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Research on collaborative service solution in ubiquitous learning environment

GZ Zhang, Q Jin

PDCAT 2005: Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, Proceedings 2005 804 - 806 2005年 [査読有り]

担当区分：最終著者

DOI

Scopus

11

被引用数

(Scopus)
Ubiquitous learning on pocket SCORM

HP Chang, WC Chang, YL Sie, NH Lin, CH Huang, TK Shih, Q Jin

EMBEDDED AND UBIQUITOUS COMPUTING - EUC 2005 WORKSHOPS, PROCEEDINGS 3823 171 - 179 2005年 [査読有り]

担当区分：最終著者

DOI

Scopus

4

被引用数

(Scopus)
Peer-to-peer based social interaction tools in ubiquitous learning environment

GZ Zhang, Q Jin, TK Shih

11th International Conference on Parallel and Distributed Systems, Vol I, Proceedings 1 230 - 236 2005年 [査読有り]

　概要を見る

This paper discusses a fundamental notion and model of ubiquitous computing technology support learning (uLearning) system. In order to increase learners' social skills and support social interaction among learners, the authors design a collection of support tools; these tools serve for three processes: encounter communication and collaboration. Furthermore, prototyping implementation of the social interaction support tools is introduced.

DOI

Scopus

7

被引用数

(Scopus)
A framework of social interaction support for ubiquitous learning

GZ Zhang, Q Jin, M Lin

AINA 2005: 19TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 2 2 639 - 643 2005年 [査読有り]

　概要を見る

This paper describes the computer supported ubiquitous learning system and the social interaction between learners. We define the ubiquitous learning with five prime attributes, and present a generalized social interaction support model for the ubiquitous learning. Moreover in order to support learners with increasing social skill, a solution for constructing social interaction in ubiquitous learning environment is designed, which includes three major functions: encounter communication and collaboration support functions.

DOI

Scopus

45

被引用数

(Scopus)
Design of peer-to-peer groupware integrated with interactive browser for active information sharing and collaboration support

R Shtykh, GZ Zhang, Q Jin

FOURTH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, PROCEEDINGS 404 - 409 2004年 [査読有り]

担当区分：最終著者
Multi-agent system for Online course content management

R Komatsu, JH Ma, Q Jin

18TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 1 (LONG PAPERS), PROCEEDINGS 1 183 - 188 2004年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
NetIsle: A hybrid peer-to-peer groupware system based on push technology for small group collaboration

R Shtykh, Q Jin

DATABASES IN NETWORKED INFORMATION SYSTEMS, PROCEEDINGS 2822 177 - 187 2003年 [査読有り]

担当区分：最終著者

DOI

Scopus
Collaborative information browser: Collecting and organizing information through group collaboration

Qun Jin, Nobuko Furugori, Katsuyoshi Hanasaki, Norifumi Asahi, Yoshiteru Ooi

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 6 170 - 174 2002年 [査読有り]

担当区分：筆頭著者

DOI

Scopus

3

被引用数

(Scopus)
Mobile Agent Platform Supports to e-Marketing

Ying Hong Wang, Qun Jin, Shih Wel Kao, Huei Yuan Chan

11th Golden West International Conference on Intelligent Systems 2002, ICIS 2002 143 - 148 2002年 [査読有り]
A push-type groupware system to facilitate small group collaboration

R. Shtykh, Qun Jin

Proceedings - 1st International Symposium on Cyber Worlds, CW 2002 354 - 359 2002年 [査読有り]

担当区分：最終著者

DOI

Scopus

3

被引用数

(Scopus)
Individualized collaboration support for online leaning communities

Q Jin

INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, VOLS I AND II, PROCEEDINGS 784 - 788 2002年 [査読有り]

担当区分：筆頭著者

DOI

Scopus
Peer-to-peer file sharing with integrated attribute descriptions in XML and an embedded database engine

S Takizawa, Q Jin

DATABASES IN NETWORKED INFORMATION SYSTEMS 2544 225 - 238 2002年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Design of a virtual community based interactive learning environment

Q Jin

INFORMATION SCIENCES 140 ( 1-2 ) 171 - 191 2002年01月 [査読有り] [国際誌]

担当区分：筆頭著者, 責任著者

　概要を見る

In this paper, we propose a conceptual framework for every-citizen learning communities based on a recently widespread Internet tool known as Multi-user dimension Object-Oriented (MOO). We discuss the design and development of a prototype system of the virtual community based interactive learning environment, which supports human-human communication in addition to human-computer communication. with emphasis on social interaction. (C) 2002 Elsevier Science Inc. All rights reserved.

DOI

Scopus

26

被引用数

(Scopus)
Design of multilingual agents for community-based collaborative virtual universities

Q. Jin, J. Huang, Z. Y. Peng

Journal of Shanghai University 5 ( SUPPL. SEPT. ) 248 - 253 2001年09月 [査読有り]

担当区分：筆頭著者
A shopping negotiation agent that adapts to user preferences

Runhe Huang, Jianhua Ma, Qun Jin

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2252 45 - 56 2001年 [査読有り]

担当区分：最終著者

DOI

Scopus

1

被引用数

(Scopus)
Computer supported social networking for augmenting cooperation

H. Ogata, Y. Yano, N. Furugori, Q. Jin

Computer Supported Cooperative Work 10 ( 2 ) 189 - 209 2001年 [査読有り]

担当区分：最終著者

DOI

Scopus

56

被引用数

(Scopus)
Optimum Order Time for a Spare Part Inventory System Modeled by a Non-Regenerative Stochastic Petri Net

JIN Qun, VIDALE Richard F., SUGASAWA Yoshio

IEICE transactions on fundamentals of electronics, communications and computer sciences 83 ( 5 ) 818 - 827 2000年05月 [査読有り]

担当区分：筆頭著者

CiNii
Design of a virtual community based interactive learning environment

Q Jin

PROCEEDINGS OF THE FIFTH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1 AND 2 5 ( 2 ) A636 - A642 2000年 [査読有り]

担当区分：筆頭著者
探索結果を利用した人脈ネットワークの活用支援の提案とその実験的評価

緒方広明, 矢野米雄, 古郡延子, 金群

情報処理学会論文誌 40 ( 2 ) 632 - 641 1999年02月 [査読有り]

担当区分：最終著者

　概要を見る

本論文では人脈ネットワークの探索結果を用いて人脈探索を支援する手法を提案する. 我々は人脈を分散型人脈活用支援システムPeCo-Mediator-IIをすでに構築したが探索結果の利用は考慮されていなかった. 探索結果を利用することにより協力者仲介者などのユーザのタイプ分けを行い人脈探索の効率化をはかる. また協力可能な人物として準協力者の役割を設けることにより新たに協力者を育成し同じ協力者への依頼の集中を避ける. さらに協力者から得たノウハウを共有することにより人脈探索の繰返しを軽減する. 最後にこれらの支援機能をPeCo-Mediator-II上に実現したシステムとその実験的評価について述べる.The exploration of social networks is essential to find capable cooperators who can help in problem-solving and in augmenting cooperation among workers in an organization. PeCo-Mediator-II is an agent based system that helps gathering, exploring, and visualizing social networks among users. This paper proposes a user model with history logs to support exploration, to share individual knowledge, and to reduce overload of cooperators. Experimental results show that the system facilitated users encounter cooperators and helped develop new relationships between users and cooperators.

CiNii
分散型人脈活用支援システムPeCo-Mediator-IIの構築 (<小特集>コンカレント・コラボレーション技術論文小特集)

緒方広明, 古郡延子, 金群, 矢野米雄

電子情報通信学会論文誌. D-I, 情報・システム, I-コンピュータ 80 ( 7 ) 551 - 560 1997年07月 [査読有り]

　概要を見る

本論文では, 通信ネットワークを利用して, 組織内のインフォーマルな人的ネットワーク(人脈)の有効利用を支援することを目的とした分散型人脈活用支援システムPeCo-Mediator-IIについて述べる. PeCo-Mediator-IIは, 名刺交換をもとにした人脈の共有活用を支援するシステムPeCo-Mediatorをネットワーク環境に拡張したものである. PeCo-Mediator-IIは, 電子メールの交換による人脈を個人ごとに蓄積し, ネットワークを介して人脈をたどり, 協力者を探し, その協力を得る過程を支援する. 本論文では, ネットワーク環境における人脈の蓄積手法と人脈の強さの数量化手法, ならびに, 人脈探索の状態遷移モデルを提案する. 更に, これらの提案に基づいて試作したシステムと, その実験的評価について述べる.

CiNii
Design issues and experiences from having lessons in text-based social virtual reality environments

Qun Jin, Yoneo Yano

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2 1418 - 1423 1997年 [査読有り]

担当区分：筆頭著者
仮想環境を利用した協調学習およびその実験的評価

金群

教育システム情報学会誌 14 ( 3 ) 29 - 36 1997年 [査読有り]

担当区分：筆頭著者

CiNii
Stochastic Petri net model of an Ethernet-based manufacturing system

Q Jin, Y Yano, Y Sugasawa

STOCHASTIC MODELLING IN INNOVATIVE MANUFACTURING 445 46 - 57 1997年 [査読有り]

担当区分：筆頭著者
Design issues and experiences from having lessons in text-based social virtual reality environments

Q Jin, Y Yano

SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5 1418 - 1423 1997年 [査読有り]

担当区分：筆頭著者
Non-regenerative stochastic Petri nets: Modeling and analysis

Q Jin, Y Yano, Y Sugasawa

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES E79A ( 11 ) 1781 - 1790 1996年11月 [査読有り]

担当区分：筆頭著者, 責任著者

　概要を見る

We develop a new class of stochastic Petri net. non-regenerative stochastic Petri net (NRSPN), which allows the firing time of its transitions with arbitrary distributions, and can automatically generate a bounded reachability graph that is equivalent to a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. Thus, it can model and analyze behavior of a system whose states include some non-regeneration points. We show how to model a system by the NRSPN, and how to obtain numerical solutions For the NRSPN model. The probabilistic behavior of the modeled system can be clarified with the reliability measures such as the steady-state probability, the expected numbers of visits to each slate per unit lime, availability, unavailability and mean time between system failure. Finally, to demonstrate the modeling ability and analysis power of the NRSPN model, we present an example for a fault-tolerant system using the NRSPN and give numerical results for specific distributions.
Modeling and analysis of agents' probabilistic behavior by a non-regenerative Stochastic Petri net

Q Jin, Y Yano, Y Sugasawa

INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4 1 187 - 192 1996年 [査読有り]

担当区分：筆頭著者
Design of a supporting tool for knowledge creation

N Furugori, Q Jin, H Ogata, Y Yano

INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4 1 580 - 585 1996年 [査読有り]

　概要を見る

Knowledge Creation from flooding information is one of the most burdensome subject we face today. We have developed a supporting tool to create knowledge for effective use of information. As a basis of the tool, we propose a cooperative framework, where user and the system cooperate each other to derive knowledge from gathered information. After presented the structure of the tool, we illustrate two major functions with examples. First one is the systematic arrangement of knowledge and the second is the elaborated search referencing knowledge base.
Distributed PeCo-Mediator: Finding partners via personal connections

H Ogata, A Goji, Q Jin, Y Yano, N Furugori

INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4 1 802 - 807 1996年 [査読有り]
COMES: Collaborative organizational memory system

H Ogata, K Tsutsumi, Q Jin, Y Yano, N Furugori

INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4 2 983 - 987 1996年 [査読有り]
PeCo-Mediator:人脈活用支援システムのモデル化と試作

緒方広明, 矢野米雄, 古郡延子, 金群

情報処理学会論文誌 36 ( 6 ) 1299 - 1309 1995年06月 [査読有り]

担当区分：最終著者

　概要を見る

人脈(Personal Connection : PeCo)は,仕事を進める上で他者の協力が必要な場合に役立つ.我々は,グループの各個人が持つ人脈の共有活用により,グループ活動の支援を目的としたシステム"PeCo-Mediator"を構築した.利用者は,共有する人物情報と人脈情報を利用して,問題解決能力をもつ人物を探し,その人物への人脈を辿り,幅広い分野の人物から協力を得ることができる.本論分では,人物探索を支援する柔軟なデータベースの枠組と人脈探索を支援する環境について述べる.柔軟なデータベースは,多様な属性をもつ人物情報が蓄積でき,利用者の情報の捉え方に適応できる.人脈の探索環境は,利用者の人脈の捉え方に適応できる人脈モデルに従い,人脈の強さを数量化して,活用できそうな人脈を視覚的に表示する.

CiNii
Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets

Q. Jin, Y. Sugasawa

Mathematical and Computer Modelling 22 ( 10-12 ) 109 - 118 1995年 [査読有り]

担当区分：筆頭著者

DOI

Scopus

9

被引用数

(Scopus)
Analyzing system reliability using non-regenerative stochastic petri nets

Y. Sugasawa, R. F. Vidale, Q. Jin

IEEE Symposium on Emerging Technologies & Factory Automation 3 399 - 406 1995年 [査読有り]

担当区分：最終著者
PeCo-Mediator: Supporting access to unknown partners for cooperation using collective personal connections - Adaptable menu-based query interface

H OGATA, Y YANO, N FURUGORI, Q JIN

SYMBIOSIS OF HUMAN AND ARTIFACT: FUTURE COMPUTING AND DESIGN FOR HUMAN-COMPUTER INTERACTION 20 ( C ) 397 - 402 1995年 [査読有り]

担当区分：最終著者

DOI

Scopus
Modeling and analysis of reliability performance for a distributed dual-processor system

Qun Jin, Yoshio Sugasawa

Computers and Industrial Engineering 27 ( 1-4 ) 497 - 500 1994年09月 [査読有り]

担当区分：筆頭著者

DOI

Scopus

2

被引用数

(Scopus)
COMPUTER-SUPPORTED ENVIRONMENT FOR COMMON EXPLOITATION OF PERSONAL INFORMATION

N FURUGORI, Q JIN, H OGATA, Y YANO

COMPUTERS & INDUSTRIAL ENGINEERING 27 ( 1-4 ) 189 - 192 1994年09月 [査読有り]

　概要を見る

Personal connections have great influences on various social activities, e.g., a business negotiation. However, data of personal connections are usually diverse, dynamic and ill-formed. In this paper, we firstly propose a model and representation for personal connections, then describe the framework to deal with ill-formed information. We discuss some key criteria on developing a common exploitation environment integrated with an adaptable data-base and user interface to support group decision. Finally, we give illustrations to show that the developed environment is effective and useful.

DOI

Scopus

1

被引用数

(Scopus)
Extended stochastic Petri Net models for systems with parallel and cooperative motions

Yoshio Sugasawa, Qun Jin, Koichiro Seya

Computers and Mathematics with Applications 24 ( 1-2 ) 119 - 126 1992年07月 [査読有り]

DOI

Scopus

3

被引用数

(Scopus)
ペトリネット表現された協調動作をするシステムの挙動解析と性能評価—システムの解析と制御

菅澤, 喜男, 金群, 瀬谷, 浩一郎

情報処理学会論文誌 33 ( 5 ) 602 - 610 1992年05月 [査読有り]

　概要を見る

一般的に協調動作をするシステムに対する稼働率などを中心とした性能評価は単独動作と協調動作が複合化するために簡単に求めることは困難であるさらに協調動作をするシステムの挙励を解析するためのモデルを構築することは協調動作をさせるための条件や順序関係を考息した上でなされなければならないペトリネットは順序関係が複雑な非同期・並列システムなどに対して順序関係を情報の流れとして表現してモデル化するのに有効な記述方法として知られているここで取り上げるモデルは非同期・並列的な動きをするシステムの理解を得るために 2台のロボットが単独で動作すると共にもう1台のロボットがコンベアと協調動作するシステムを良く見掛ける一例としてペトリネットで記述しモデル化するモデル化したシステムにマルコフ再生過程を適用し極限確率を求めて協調動作をするシステムの稼働率を定義して各システムの要素あるいは要素同士が協調動作をしている場合の稼働率を求めると共に競合率や並行率を定義し確率的諸量を求めてシステムの性能評価となり得る新たな基準を示す最後に性能評価としてペトリネット記述されたモデルの各遷移が発火する時間に具体的な分布と数値導入して協調動作をするシステムの性能評価のあり方について具体的な検討を加える

CiNii
分散処理におけるシンク発生の確率モデルと挙動解析

金群, 菅沢喜男, 瀬谷浩一郎

電子情報通信学会論文誌. A, 基礎・境界 = The IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Japanese edition). A / 電子情報通信学会編 75 ( 3 ) p658 - 660 1992年03月 [査読有り]

担当区分：筆頭著者

　概要を見る

記事分類: データ処理・計算機器

CiNii
Analysis of Stochastic Petri Net model with non-exponential distributions using a generalized Markov Renewal Process

Qun Jin, Yoshio Sugasawa, Koichiro Seya

Microelectronics Reliability 31 ( 5 ) 933 - 939 1991年 [査読有り]

担当区分：筆頭著者

DOI

Scopus
Modelling and analysis of a semaphore system by an extended stochastic petri net

Yoshio Sugasawa, Qun Jin, Jian Ting Zhang, Koichiro Seya

International Journal of Systems Science 22 ( 1 ) 217 - 224 1991年01月 [査読有り]

DOI

Scopus

3

被引用数

(Scopus)
Probabilistic behavior and reliability analysis for a multi-robot system by applying Petri net and Markov renewal process theory

Qun Jin, Yoshio Sugasawa, Koichiro Seya

Microelectronics Reliability 29 ( 6 ) 993 - 1001 1989年 [査読有り]

担当区分：筆頭著者

DOI

Scopus

11

被引用数

(Scopus)

▼全件表示

書籍等出版物

Device-to-device based proximity service: Architecture, issues, and applications

Yufeng Wang, Athanasios V. Vasilakos, Qun Jin

CRC Press 2017年 ISBN: 9781498724180

　概要を見る

D2D-based proximity service is a very hot topic with great commercial potential from an application standpoint. Unlike existing books which focus on D2D communications technologies, this book fills a gap by summarizing and analyzing the latest applications and research results in academic, industrial fields, and standardization. The authors present the architecture, fundamental issues, and applications in a D2D networking environment from both application and interdisciplinary points of view.

DOI
Distance Education Environments and Emerging Software Systems: New Technologies, Advances in Distance Education Technologies series

Q. Jin( 担当：編集)

IGI Global 2011年
Intelligent Learning Systems and Advancements in Computer-Aided Instruction: Emerging Studies, Advances in Distance Education Technologies series

Q. Jin( 担当：編集)

IGI Global 2011年
Enabling Society with Information Technology

Q. Jin, J. Li, N. Zhang, J. Cheng, C. Yu, S. Noguchi

Springer 2002年
Proceedings of Sixth International Conference of Educational Innovation through Technology

J. Liu, S. Nishimura, H. Zhang and Q. Jin (Eds.)

IEEE Computer Society CPS 2017年
Proceedings of IEEE DASC-PICom-DataCom-CyberSciTec 2016

K. Wang, Q. Jin

IEEE Computer Society CPS 2016年
Proceedings of Fifteenth International Conference on Ubiquitous Computing and Communications and Eighth International Symposium on Cyberspace Safety and Security

J.G. Blas, J. Carretero, I. Ray, Q. Jin, N. Georgalas (Eds.)

IEEE Computer Society CPS 2016年
Human Centric Technology and Service in Smart Space: HumanCom 2012, Lecture Notes in Electrical Engineering, Vol. 182

J.J. Park, Q. Jin, S.S. Yeo, B. Hu

Springer 2014年
Frontier and Future Development of Information Technology in Medicine and Education: ITME 2013, Lecture Notes in Electrical Engineering, Vol. 269

S. Li, Q. Jin, X. Jiang, J.J. Park

Springer 2013年
Technology Enhanced Learning: Quality of Teaching and Educational Reform, Communications in Computer and Information Science Series, Vol. 73

M.D. Lytras, P.O. De Pablos, D. Avison, J. Sipior, Q. Jin (Eds.).

Springer 2010年
Proceedings of Second IEEE Asia-Pacific Service Computing Conference

J. Li, M. Guo, Q. Jin

IEEE Computer Society CPS 2007年

▼全件表示

共同研究・競争的資金等の研究課題

知能IoTを活用した東アジアにおける高齢者のライフスタイルと福祉の強化

日本学術振興会日中韓フォーサイト事業

研究期間:

2020年08月

-

2025年07月

中澤仁
ソーシャルワーク実習教育におけるICTの効果的活用

日本学術振興会科学研究費助成事業

研究期間:

2021年04月

-

2025年03月

新保祐光, 金群, 宮崎牧子, 石川到覚, 金潔

　概要を見る

１. １年目は１）令和２、３年度に本学科でおこなったICTをもちいた学内実習の検証、２）海外におけるICTをもちいた実習教育の先駆事例の検討、３）ICT教育の方法と有用性の理解の深化を研究課題とした。１）２）に関しては、社会福祉実践現場でのICTの先駆的活用事例も含めて、第44回大正大学社会福祉学会「ポスト・コロナの地域を見据えるソーシャルワーク実践とICT活用」のなかで、基調講演やシンポジウムをおこない検討することが出来た。
そこでは、感染症予防のために直接関わることが出来ない場合のツールとしてICTが有用であることが示された。その有用性は、直接関わらないため感染リスクの低下という安全性、移動時間の短縮等による効率性、意思表明の機会の確保による権利擁護、感情表出の確保による情緒的支持などがある。限界としては、非言語等、対面で会えるときよりは情報が少なくなるため、ディスコミュニケーションが起きやすいことである。
課題としては、ICT教育の方法と効果の検討については、研究メンバー間での検討はある程度行えたが、外部へのアウトプットまでは至らなかった。
２. このほかソーシャルワークのICT活用の研究として、オンラインによるスーパービジョンの効果を検討するために、スーパービジョングループを作り、毎月１回オンライングループスーパービジョンを実施している。
その内容を毎週を録画し、話し合われた内容を分析することで、オンラインスーパービジョンの効果を検討するためのプロセスである。約１年間実施しており、出来れば同じ参加者のコメントの変化を検討することで、オンラインスーパービジョンの効果と限界を検討したい。
人間科学的アプローチによる未病の可視化と東洋医学理念に基づく健康増進モデル構築

井深大基金東洋医学に関する人間科学的研究プロジェクト

研究期間:

2022年04月

-

2025年03月

金群
健康データの分析による健康増進で中長期的にまちを発展させる事業

内閣府デジタル田園都市国家構想推進交付金

研究期間:

2022年04月

-

2025年03月

埼玉県皆野町, 早稲田大学人間総合研究センター, 株式会社アイネス総合研究所
ブロックチェーンと連合学習による個人主導の高信頼データ共有

早稲田大学－情報通信研究機構マッチング研究支援事業

研究期間:

2021年04月

-

2023年03月

金群
障害情報の電子化による次世代地域・福祉サービス連携の創出

JST 戦略的創造研究推進事業（社会技術研究開発）「SDGｓの達成に向けた共創的研究開発プログラム」

研究期間:

2019年11月

-

2021年10月

巖淵守
高齢者生活支援のための脈データ分析と健康管理指向脈診基盤モデル構築

井深大基金東洋医学に関する人間科学的研究プロジェクト

研究期間:

2016年04月

-

2019年03月

金群
個人ビッグデータの持続的活用を実現するための基盤モデルとメカニズムの研究

早稲田大学特定課題A

研究期間:

2014年04月

-

2015年03月

金群
Growing Campusの基盤をなす分散協調型知識情報共有システムの構築

早稲田大学人間総合研究センターシーズ型研究課題

研究期間:

2010年04月

-

2013年03月

西村昭治
実世界での実験・実習・体験とu-Learningの融合

科学研究費補助金基盤研究(A)

研究期間:

2007年04月

-

2010年03月

矢野米雄

　概要を見る

携帯情報端末、センサ、マルチメディアコンテンツやワイヤレスネットワークといったユビキタス技術を用い、「現実世界と仮想世界」、「講義と実践」のギャップを埋めるユビキタス学習システムを開発・評価した。
人間中心の分散協調型知識情報共有システムの研究開発とｅスクールでの利用

早稲田大学人間総合研究センターシーズ型研究課題

研究期間:

2004年04月

-

2007年03月

金群
ブロードバンドを利用した新しい高等教育の有機的モデルとプロトタイプの開発

科学研究費補助金基盤研究(B)

研究期間:

2003年04月

-

2007年03月

向後千春

　概要を見る

フルオンデマンドによるeラーニングのコースを実質的に成果のあるものにするためには、教員、コーチ、サポートスタッフの3種類の人的資源がそれぞれに割り当てられた仕事をこなすこと、そしてラーニング・マネジメント・システム(LMS)を含むeラーニングシステムが学習者の学習を促進するような機能をもつことが必要である。
教員の仕事は大きく分けて、コースの設計、実施、評価と改善の3つに分類できる。eラーニングになってとりわけ重要なことは、コースの設計と詳細化における仕事に重心が移ることである。eラーニングにおける教員の仕事はコースの設計と詳細化という部分に重心が移った。それによってコースの実施段階では教員を補佐し、実質的に授業運営の大きな部分を担う人材が必須のものとなった。それがコーチである。コーチの仕事は、大きく分けて、学習活動の促進、雰囲気と規範作り、議論プロセスの主導の3つである。LMSについては、有償・無償のものを含めてさまざまな種類のものが利用できる。最低限、ビデオ配信、BBS、レポート・テストのやりとりができるシステムであればeラーニングを実施することができる。しかし、eラーニング授業をもっと着実なものにするためには、それぞれの機能についていっそうの工夫が必要である。将来的な学習環境について述べる。現在の環境は、学習者がLMSにログインして、そこで学習のリソースを見て、自分の手元でノートを取るというような形になっている。しかし、将来的には、Webブラウザを開けば、すぐにそこが自分の学習用のワークスペースになっているようなイメージにしたい。
環境メディアとして仮想現実システムを利用したラーニングコミュニティの研究開発

科学研究費補助金基盤研究(B)

研究期間:

2000年04月

-

2003年03月

金群

　概要を見る

高度情報社会において、知識の更新のペースがますます速めており、従来の学校、大学での教育では対応できなくなりつつある。社会において、生涯を通じた多様な学習者を対象とする教育/学習システムが求められている。
本研究は、Every-Citizen Learning Communityという基本理念をもとに、インターネットの提供する普遍的で自由なデジタルコミュニケーション環境を生かしながら、多様な学習者に対して広く開かれたコミュニティ型教育/学習システム-ラーニングコミュニティ(学びの共同体)を提案し、環境メディアとして仮想現実システムを用いて、実社会のニーズに即したシステムを構築することを目指したものである。
本研究では、MOO(Multi user dimension Object Oriented)と呼ばれるソーシャル仮想現実システムを新たな環境メディアとしてとらえ、モデル化を行うとともに、他のデジタルメディアとの融合を図り、ラーニングコミュニティを構築する基盤技術として協調仮想環境を開発している。さらに、ラーニングコミュニティの仮想環境とインターネットにおける膨大な情報資源や各種機能との統合、多様な学習者の挙動を考慮した協力支援エージェント、利用者の行動に柔軟に適応するインターフェース、個人のニーズに対応した協調支援ツール、ピア・ツー・ピアによるグループ協同作業支援と情報共有、従来の教室にない学習支援環境とコンテンツ、仮想環境の分散化などについて研究開発を行った。
本研究は、21世紀における革新的な教育/学習システム・方法の確立およびネットワーク情報社会において生涯を通じた人間の知識取得、更新のための新たな知識資源となることが期待できる。
社会ネットワークに着目したエージェント指向協調学習支援システムの研究開発

科学研究費補助金基盤研究(B)

研究期間:

2000年04月

-

2002年03月

緒方広明

　概要を見る

本研究の目的は、エージェント技術を用いて個人がもつ社会ネットワークを通じてユーザ同士が新たに出会い、知識ネットワークの構成し、新たな知識を創造し、それを蓄積・活用していける協調学習環境を構築することである。つまり、本研究では、社会ネットワークを単に情報や知識の伝達手段だけでなく、一人一人の個人の能力の開発手段と捉えており、各個人の知識ネットワークの成長と知識の創生の支援を目指すものである。
本研究では、各ユーザのエージェントが電子メールの交換をもとに、社会的ネットワークを蓄積し、そのデータを元にネットワークを探索・交渉を支援するシステムを開発した。また、Web上のデータをもとに社会的ネットワークを発見し、それを視覚化するシステムも構築した。それぞれ評価を行い、その有効性を検証した。さらに関連研究として、社会的ネットワークの構成につながる人との出会いを支援するKnowledge Awarenessを視覚的に提供するKnowledge Awareness Mapの構築と、エージェント技術を利用して、学習者がいつでもどこででも非同期に参加できる講義・教室型の協調学習環境として、非同期型バーチャルクラスルームを開発した。また、作文教育において、ネットワークを通じて添削作業が可能な協同学習支援システムを構築した。
インターネット技術の発展は著しく、Java, VRMLといった様々なネットワークプログラミング技術や、Agent Tc1等のエージェント技術が開発されている。本研究は、社会ネットワークという、個人にとって非常に貴重な無形財産をネットワークを利用して蓄積し、エージェント技術を用いて、その情報を有効に活用し、個人個人の能力を伸ばし、組織の発展を目指すものであり、次世代の高度情報システムとして、社会への貢献が期待されるものである。
エージェントを用いた日本語教育のための柔軟な協調学習環境の研究

科学研究費補助金基盤研究(B)

研究期間:

1997年04月

-

2001年03月

矢野米雄

　概要を見る

本研究の目的は,エージェント技術を用いて,日本語教育のための柔軟な協調学習環境を構築することである.我々は,その学習対象として,作文教育を選び,ネットワークを通じて添削作業が可能な学習支援システムを構築した.学習者と教師が協調しながら行う添削作業を,コンピュータを用いて分散環境で可能とするシステムCoCoA(Communicative Correction Assisting System)を構築した.また,実験によりCoCoAの学習環境における添削に必要となる添削記号や支援機能を抽出した.その考察結果をもとに,添削文章の交換方式としてCCML(Communicative Correction Markup Language)を提案した.さらに,システムを試作し,評価実験を行い,CoCoAとCCMLの有効性を示した.
また,近年,インターネットの普及により,時間・場所の制約を越えて,様々な国の人々がサイバースペース上で容易にコミュニケーションできるようになってきた.本研究では,ソフトウェアエージェントの介在により,サイバースペースでの言語学習を支援する学習環境Anckleを提案した.Anckleは,コミュニカティブアプローチに基づき,サイバースペース内での母語話者とのコミュニケーションによる言語学習を支援する.また,外国語学習で大きなで問題となる言語転移に着目して,エージェントがコミュニケーションに介入し,学習者の理解状態に合わせて教授を行う.我々は,コミュニケーションギャップモデル(CGM)を提案し,中国人による日本語学習を支援するシステムを試作した.
インターネットを利用した日本語学習マルチメディア辞書の構築

科学研究費補助金基盤研究(B)

研究期間:

1997年04月

-

2001年03月

矢野米雄

　概要を見る

我々は,WWWに代表されるインターネットを利用したオープンで拡張可能な日本語学習用電子辞書システムの研究として,待遇表現学習システムJecy,漢字熟語辞書システムKIDS-II,擬音語擬態辞書システムJamios,漢字学習支援システムJUPITERおよびAnckleのプロジェクトを進めた.Jecyは対人関係に着目した待遇表現学習支援システムであり,待遇表現知識ベースと文化的な差異による対人関係の捉え方をフォローする環境を実現した.そして,待遇表現辞書Jedyへと応用した.JAMIOSは,擬音語・擬態語を対象にマルチメディア情報を用いて,文化的な差異による意味理解と,マルチメディアをキーにした柔軟な電子辞書を実現した.KIDS-IIは,漢字熟語の類推を支援する辞書システムであり,漢字の出現頻度に着目した任意の漢字熟語に対する読み候補導出機構を実装した.JUPITERは,KIDS-IIを応用したものであり,情報フィルタリング技術を応用して学習漢字を選定する漢字選定フィルタリングを実装した.Anckleは,日本語と中国語における漢字の意味差異を考慮した学習支援を行う学習支援システムである.本システムは,日中の差異知識を扱う電子辞書を持ち,ソフトウェアエージェントを利用して,学習者と母語話者のコミュニケーションを支援する.これらのシステムはWindows上で動作し,ソフトウェアコンポーネント化によるインターネット対応の枠組みで実装した.また,各システムは日本語教育現場での試用評価を行い,良好な結果が得られた.
協調学習を支援するためのテキスト型仮想現実の構成に関する研究

科学研究費補助金奨励研究(A)

研究期間:

1998年04月

-

2000年03月

金群

　概要を見る

近年、情報・通信技術の急速な発展に伴い、ネットワークを介した仮想コミュニティ、仮想オフィス、仮想キャンパスが次々と現われ、このような仮想空間に入り込んで、仕事したり学習したりすることは現実のものとなりつつ、人と社会全般の活動に新たな変化をもたらしている。一方、知識を人から人へ伝達するための「もの」としてではなく、社会的な相互作用の結果として形成されるものととらえる立場から協調学習の有効性が高く評価されている。本研究は、MOO(Multi user dimension Object-Oriented)と呼ばれるテキスト型仮想現実を用いて、学習者の行動に柔軟に適応する仮想空間のモデルを考案し、仮想空間の系統的な構成法を開発している。また、学習者の能動性を重視した協調学習理論に基づき、仮想大学の基本枠組みを提案し、仮想クラスルームの基本的要件を明らかにしている。さらに、教育・学習において、インターネット上にある豊富な情報資源を活用するために、MOOの仮想環境とWEBサーバの統合を行うとともに、マルチメディアも利用できるようにMOO環境を改善し、専用GUIインタフェースを構築した。また、仮想空間におけるコミュニケーション、インタラクション、コラボレーションを促進する自律的に振る舞い可能なソフトウェアエージェントを試験的に導入し、多様な学習者による協調学習を積極的に支援する。本研究では、プロトタイプシステムを構築し、初歩的な実験評価を行い、従来の実験結果と比較した結果、本研究によって得られる創出的学習効果が期待できる。また、本研究は、協調的な仮想大学の基盤技術として適用できる。
協調学習のための能動型データベースシステムの研究

科学研究費補助金重点領域研究

研究期間:

1997年04月

-

1998年03月

矢野米雄

　概要を見る

本研究の目的は,コンピュータとネットワークを利用した学習者中心の協調学習を実現するための能動型データベースシステムを開発することである.本研究では,データベースの内容と各学習者の操作履歴情報を有効活用して,協調学習を誘発する適切なアウェアネス情報を生成するための高度な協調能動型データベースを構築した.さらに,協調学習における能動型データベースの可能性を探るため,テキスト型仮想現実環境MOOを利用した協調学習環境と文章構造化技術を利用した協調学習環境の構築を行った.
(1)Knowledge Awareness Filtering
Knowledge Awareness (KA)は,“知識に気付く"という意味であり,学習者に対して,討論のきっかけとなる知識や他の学習者の行動に気付かせる情報である.KAの目的は,学習者間の討論の誘発であるが,学習者の要・不要に関係なく情報を提供するため,学習の妨げとなることがある.従って,本研究では,学習者の学習状態に応じて,KA情報を提供するFiltering機構を構築した.実験的な評価の結果,本手法が,学習意欲を軽減させることなく,協調学習へのきっかけを適切に与れることが分かった.
(2)SGMLを利用した添削作業に基づく協調学習環境
学習者と教師が協調しながら行う添削作業を,コンピュータを用いて分散環境で可能とするシステムCoCoAを提案した.また,実験によりCoCoAの学習環境における添削に必要となる添削記号や支援機能を抽出した.その考察結果をもとに,添削文章の交換方式としてCCMLを提案した.さらに,システムを試作し,評価実験を行い,CoCoAとCCMLの有効性を示した.
(3)テキスト型仮想現実環境MOOを利用した協調学習環境
本研究では,MOOを用いて構築された仮想環境及びそれを利用した協調学習とその実験的な評価を行った.我々は,仮想的な協調学習環境VirsicleとそのグラフィカルユーザインタフェースMooErを構築した.この仮想学習環境は,バーチャルクラスルームとして試用し,試験を含むすべての授業,演習がそこで行われた.半年にわたる実験的な評価の結果,Virsicleは協調学習に適し,学習者の積極的な参加による学習効果の向上が期待できることがわかった.

▼全件表示

Misc

特集「人間中心のユニバーサル/ユビキタス・ネットワークサービス」の編集にあたって

金群, 荒金陽助

情報処理学会論文誌 49 ( 1 ) 2008年11月

CiNii
Phenome-wide causal proteomics enhance systemic lupus erythematosus flare prediction: A study in Asian populations

Liying Chen, Ou Deng, Ting Fang, Mei Chen, Xvfeng Zhang, Ruichen Cong, Dingqi Lu, Runrun Zhang, Qun Jin, Xinchang Wang

2024年11月

　概要を見る

Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease
characterized by unpredictable flares. This study aimed to develop a novel
proteomics-based risk prediction model specifically for Asian SLE populations
to enhance personalized disease management and early intervention. Methods: A
longitudinal cohort study was conducted over 48 weeks, including 139 SLE
patients monitored every 12 weeks. Patients were classified into flare (n = 53)
and non-flare (n = 86) groups. Baseline plasma samples underwent
data-independent acquisition (DIA) proteomics analysis, and phenome-wide
Mendelian randomization (PheWAS) was performed to evaluate causal relationships
between proteins and clinical predictors. Logistic regression (LR) and random
forest (RF) models were used to integrate proteomic and clinical data for flare
risk prediction. Results: Five proteins (SAA1, B4GALT5, GIT2, NAA15, and RPIA)
were significantly associated with SLE Disease Activity Index-2K (SLEDAI-2K)
scores and 1-year flare risk, implicating key pathways such as B-cell receptor
signaling and platelet degranulation. SAA1 demonstrated causal effects on
flare-related clinical markers, including hemoglobin and red blood cell counts.
A combined model integrating clinical and proteomic data achieved the highest
predictive accuracy (AUC = 0.769), surpassing individual models. SAA1 was
highlighted as a priority biomarker for rapid flare discrimination. Conclusion:
The integration of proteomic and clinical data significantly improves flare
prediction in Asian SLE patients. The identification of key proteins and their
causal relationships with flare-related clinical markers provides valuable
insights for proactive SLE management and personalized therapeutic approaches.
Evolutionary Causal Discovery with Relative Impact Stratification for Interpretable Data Analysis

Ou Deng, Shoji Nishimura, Atsushi Ogihara, Qun Jin

2024年04月

　概要を見る

This study proposes Evolutionary Causal Discovery (ECD) for causal discovery
that tailors response variables, predictor variables, and corresponding
operators to research datasets. Utilizing genetic programming for variable
relationship parsing, the method proceeds with the Relative Impact
Stratification (RIS) algorithm to assess the relative impact of predictor
variables on the response variable, facilitating expression simplification and
enhancing the interpretability of variable relationships. ECD proposes an
expression tree to visualize the RIS results, offering a differentiated
depiction of unknown causal relationships compared to conventional causal
discovery. The ECD method represents an evolution and augmentation of existing
causal discovery methods, providing an interpretable approach for analyzing
variable relationships in complex systems, particularly in healthcare settings
with Electronic Health Record (EHR) data. Experiments on both synthetic and
real-world EHR datasets demonstrate the efficacy of ECD in uncovering patterns
and mechanisms among variables, maintaining high accuracy and stability across
different noise levels. On the real-world EHR dataset, ECD reveals the
intricate relationships between the response variable and other predictive
variables, aligning with the results of structural equation modeling and
shapley additive explanations analyses.
Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-Attention

Ou Deng, Qun Jin

2023年08月

　概要を見る

Addressing missing data in complex datasets including electronic health
records (EHR) is critical for ensuring accurate analysis and decision-making in
healthcare. This paper proposes dynamically adaptable structural equation
modeling (SEM) using a self-attention method (SESA), an approach to data
imputation in EHR. SESA innovates beyond traditional SEM-based methods by
incorporating self-attention mechanisms, thereby enhancing model adaptability
and accuracy across diverse EHR datasets. Such enhancement allows SESA to
dynamically adjust and optimize imputation and overcome the limitations of
static SEM frameworks. Our experimental analyses demonstrate the achievement of
robust predictive SESA performance for effectively handling missing data in
EHR. Moreover, the SESA architecture not only rectifies potential
mis-specifications in SEM but also synergizes with causal discovery algorithms
to refine its imputation logic based on underlying data structures. Such
features highlight its capabilities and broadening applicational potential in
EHR data analysis and beyond, marking a reasonable leap forward in the field of
data imputation.
地域・福祉サービスのデータ連携に向けた障害情報の電子化インタフェースに関する検討: Study on Data Collaboration and Digital Inclusion of Local/Social Services for People with Disabilities

35 ( 1 ) 97 - 108 2022年03月
High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection

Yunxiang Li, Yifan Zhang, Yaqi Wang, Shuai Wang, Ruizi Peng, Kai Tang, Qianni Zhang, Jun Wang, Qun Jin, Lingling Sun

2021年03月

　概要を見る

As the most economical and routine auxiliary examination in the diagnosis of
root canal treatment, oral X-ray has been widely used by stomatologists. It is
still challenging to segment the tooth root with a blurry boundary for the
traditional image segmentation method. To this end, we propose a model for
high-resolution segmentation based on polynomial curve fitting with landmark
detection (HS-PCL). It is based on detecting multiple landmarks evenly
distributed on the edge of the tooth root to fit a smooth polynomial curve as
the segmentation of the tooth root, thereby solving the problem of fuzzy edge.
In our model, a maximum number of the shortest distances algorithm (MNSDA) is
proposed to automatically reduce the negative influence of the wrong landmarks
which are detected incorrectly and deviate from the tooth root on the fitting
result. Our numerical experiments demonstrate that the proposed approach not
only reduces Hausdorff95 (HD95) by 33.9% and Average Surface Distance (ASD) by
42.1% compared with the state-of-the-art method, but it also achieves excellent
results on the minute quantity of datasets, which greatly improves the
feasibility of automatic root canal therapy evaluation by medical image
computing.
Enabling the Social Internet of Things and Social Cloud

Weishan Zhang, Qun Jin, Didier El Baz

2019年04月

　概要を見る

Social Internet of Things are changing what social patterns can be, and will
bring unprecedented online and offline social experiences. Social cloud is an
improvement over social network in order to cooperatively provide computing
facilities through social interactions. Both of these two field needs more
research efforts to have a generic or unified supporting architecture, in order
to integrate with various involved technologies. These two paradigms are both
related to Social Networks, Cloud Computing, and Internet of Things. Therefore,
we have reasons to believe that they have many potentials to support each
other, and we predict that the two will be merged in one way or another.

DOI
Growing Campusの基盤をなす分散協調型知識情報共有システムの構築

西村昭治, 金群, 尾澤重知

人間科学研究 26 ( 2 ) 221 - 222 2013年09月

CiNii
研究室だより人間情報科学科・ネットワーク情報システム学研究室(Lavoratory of Network Information Systems)

金群

人間科学研究 25 ( 1 ) 44 - 46 2012年

CiNii
Web標準の進化に対応したWebオーサリング手法の提案と実装—Proposal and Implementation of a Web Authoring Method Corresponding to Web Standards Evolution

Zhu, Jin, Nakazato, Hidenori, Urano, Yoshiyori, Jin, Qun, 朱, 槿, 中里, 秀則, 浦野, 義頼, 金, 群

GITS/GITI Research Bulletin 2010-2011 25 - 35 2011年10月

CiNii
Web標準の進化に対応したWebオーサリングツールの開発—The Development of Web Authoring Tool Corresponding to Web Standards Evolution

朱槿, 浦野義頼, 金群

日本ソフトウェア科学会大会論文集 / 日本ソフトウェア科学会編 27 1 - 17 2010年09月

CiNii
Wikipediaカテゴリより抽出されたコンセプトクラスに基づく情報推薦モデル

陳健, シュティフロマン, 金群

人工知能学会第二種研究会資料 2009 ( SWO-020 ) 10 2009年01月

　概要を見る

本研究では、Wikipedia のカテゴリ情報から抽出されたコンセプトクラスに基づく情報推薦モデルを提案する。先ず、Wikipedia からコンセプト構造とコンセプトを表現するインデックス情報を抽出し、それに基づいて、利用者の情報アクセス行動のデータをコンセプトクラスごとに収集するとともに、ショート、ミディアム、ロングといった期間に分けてそれらのデータを解析し、各コンセプトの期間ごとの確率を算出し、利用者に情報を推薦するためのモデルを構築する。

DOI CiNii
特集「人間中心のユニバーサル/ユビキタス・ネットワークサービス」の編集にあたって—巻頭言

金群, Jin, Qun

情報処理学会論文誌 49 ( 1 ) 1 2008年01月

CiNii
スライド教材の編集による教育・学習支援環境の試作

松浦健二, 金西計英, 矢野米雄, 金群

電子情報通信学会和文論文誌D Vol.91-D,No.2 259 - 268 2008年 [査読有り]
利用者の情報アクセス行動を推定する逐次適応モデル—Gradual adaptation model for estimation of human information access behavior—データベースシステムグループウェアとネットワークサービス

陳健, Roman Y. Shtykh, 金群

情報処理学会研究報告 = IPSJ SIG technical reports 2008 ( 7 ) 19 - 24 2008年01月

CiNii
自己拡張を実現するためのデジタルメディアの可能性

中舘俊一, シュティフロマン, 金群

ワークショップ2007 （GN Workshop 2007) 論文集 2007 69 - 70 2007年11月

　概要を見る

本稿は、「人間は常に自己拡張を求める」という考えに立脚し、デジタルメディア利用によっていかに自己拡張が行えるかの可能性について論じるものである。まず、人間の特性から自己拡張とはどういうものかについて考える。次に、近年大きな注目を浴びているモバイルSNSを自己拡張ツールとしてとらえ考察を行い、人間の潜在的な能力を究極的に発揮し、自己拡張を実現するためのデジタルメディアの創出への議論を投げ掛ける。

CiNii
時空間情報を基につながるCubicSNSの提案

池内希, 陳泓, 金群

ワークショップ2007 （GN Workshop 2007) 論文集 2007 65 - 66 2007年11月

　概要を見る

現在、ソーシャルネットワーキングサービス (SNS) では多くのコミュニケーションが発生している。これらのサービスでは主に、友人関係 (FOAF) を基にしたネットワークが構築されている。本文では、FOAF に加えて RFID や GPS を活用し、空間・時間情報の共有により新たな関係を発生させる CubicSNS を提案する。

CiNii
モバイル検索のためのスクロールなしのインタフェース

シュティフロマン, 陳健, 金群

ワークショップ2007 （GN Workshop 2007) 論文集 2007 67 - 68 2007年11月

　概要を見る

ウェブ検索サービスに対するユーザの満足度やユーザビリティにおいて、インタフェースはサーチエンジンの性能改良や機能増強と並ぶ極めて重要な要素である。とくに画面の小さな携帯電話や PDA 向けのウェブ検索には決定的な要素となることが考えられる。本稿では、モバイル検索を対象としたスクロールなしのインタフェースを提案し、試作および初歩的な実験結果をもとに、従来のインタフェースと比べながらその特徴について論じる。

CiNii
WebサービスのMashupによる情報アクセス共有支援環境の試作

陳泓, 池内希, 金群

ワークショップ2007 （GN Workshop 2007) 論文集 2007 95 - 100 2007年11月

　概要を見る

本研究では、情報をアクセス・集約する個人ポータルとしてユビキタス・パーソナル・スタディ UPS(Ubiquitous Personal Study，ユビキタス個人書斎) を提案し、情報の一括管理・組織化・共有化を図る。個々の UPS はクロース SNS (XSNS) を通して相互連結により友人関係を確立し、情報共有、情報推薦、友人推薦などの機能の基盤となる。システムと各モジュールは OSS をベースに構成され、必要に応じてカスタマイズする。本研究では、Web サービスを利用して省力化のみならず相互運用可能な Mashup 技術による実装を試みる。
We propose Ubiquitous Personal Study (UPS), a framework of personal information portal to support accessing, managing, organizing, sharing and recommending information. In this paper, we focus on discussing the issues on how to implement it with Web services mashup technology and Open Source Software.

CiNii
ウェブ検索挙動に基づいた共通の興味をもつユーザグループの動的形成と参加推薦方式の提案

シュティフロマン, 金群

ワークショップ2006 （GN Workshop 2006) 論文集 2006 57 - 58 2006年11月

　概要を見る

本稿では、自動生成された個人プロフィールからグループプロフィールを構築することによる、共通の興味をもつグループの形成仕組みおよび、ウェブ検索挙動に基づいて参加グループを推薦する新たな方式を提案する。

CiNii
Wikiの普及と個性化の保持

陳健, 金群

ワークショップ2006 （GN Workshop 2006) 論文集 2006 67 - 68 2006年11月

　概要を見る

生まれてからわずか 10 年間、多くの Wiki クローンが作成され、様々なプラットフォームに移植され、活用されている。一方、多様性をもつ Wiki は、異なるクローンを超えた情報共有に不便を与えている。また、Wiki の標準化をしようとする動きが活発になっている。本稿では、Wiki の普及と個性化・多様性の保持について論じる。

CiNii
パーソナライズドWeb検索における適合性フィードバックの増大する役割－－Better Search & Sharingの試み－－

シュティフロマン, 金群

ワークショップ2006 （GN Workshop 2006) 論文集 2006 109 - 113 2006年11月

　概要を見る

情報の急増する時代に生きる我々にとって、周囲の莫大な量の情報に対して自らを順応させたり、その情報量を管理したりすることはますます困難になってきている。我々が現在実感している情報氾濫は将来も進行すると予想されるので、周囲の情報の扱い方をより深く理解することは重要であろう。そこで、我々は新しい情報を整理したり、個人のニーズに最もマッチする情報を検索する新たな方法を模索している。本論文では、情報検索の性能を一層改善させるために、ウェブ検索においてますます大きな役割を果たすようになってきている適合性フィードバックについて論じ、それを積極的に活用するようにした、「より良い情報検索・共有」を提供する仕組み BESS（BEtter Search & Sharing）の進化を示す。
We are living in the era of fast information growth when we are hardly able to self-orientate in the volume of information surrounding us and manage it. In the situation of huge information overflow that we are experiencing already now and will be experiencing sharply in the future we are trying to better understand how to treat information around us looking for new methods of organizing new information pieces or retrieving slices of information best matching our current needs. In this paper we are examining the growing role of relevance feedback to improve information retrieval in Web search systems and representing a shift to its active use in BESS (BEtter Search and Sharing) collaborative search system.

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Cross SNS を活用した情報アクセス共有支援環境の提案

陳泓, 竹井菜奈子, 張国珍, 金群

ワークショップ2006 （GN Workshop 2006) 論文集 2006 103 - 108 2006年11月

　概要を見る

本研究では、個人化されたデジタル仮想書斎 UPS（Ubiquitous Personal Study，ユビキタス個人書斎）を用いた情報アクセス共有支援環境を提案する。UPS は FOAF (Friend Of A Friend ) に基づいた Cross Social Networking Service (XSNS) を通して相互に連結され、その連結レベルは利用者間関係の親密度合いによりさらに５つのレベルに細分化される。それによって、情報アクセスのコントロールを可能にするとともに、インターネットを通して友人同士やグループとの連携を容易にし、異なるプラットフォームを越えた共同作業のための情報交換共有が柔軟に行える。
In this paper, we propose and design a supportive information access and sharing environment based on Ubiquitous Personal Study (UPS), a personalized virtual study. UPS is linked each other by Cross Social Networking Service (XSNS), based on the FOAF (Friend Of A Friend) relationships, which are further divided into five access levels that depend on the familiar extend. UPS utilizing XSNS makes it possible to control information access, easy to connect friends and groups across Internet, and flexible to share data across platforms for collaborative works.

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P2Pネットワークを用いた異なるメディア・プラットフォーム間における情報共有の提案(情報共有)

飯村卓也, 吉見圭司, 竹井菜奈子, 張国珍, 金群

情報処理学会研究報告. GN, [グループウェアとネットワークサービス] 2006 ( 60 ) 25 - 30 2006年05月

　概要を見る

本研究では、BlogやWiki、XOOPSといった個人が自由に情報を発信し交換できるメディア・プラットフォームを、ピア・ツー・ピア(P2P)ネットワーク環境で連携する情報共有支援環境を提案し、個人や少人数のグループから人数の制限がないオープンなコミュニティを柔軟に形成でき、オフラインでも情報の作成や編集が可能な協調分散型情報共有システムの試作を試みた。

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ライフタイムにわたるユビキタス情報マネジメントに関する考案（ポジションペーパー）

金, 群, Q.Jin

ワークショップ2005 （GN Workshop 2005) 論文集 2005 53 - 54 2005年11月

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分散型P2P ネットワークと集中型メディアツールの統合によるスケーラブルな情報共有システムの実現

張国珍

ワークショップ2005 （GN Workshop 2005) 論文集 2005 59 - 60 2005年11月

　概要を見る

本研究では分散型 P2P ネットワーク技術と集中型情報メディアツールが融合した情報共有手法を提案する。本手法では、個人情報発信ツール Blog 及びグループ共同編集ツール Wiki と P2P ネットワークを統合させ、ユーザの増減によるスケールアップ・スケールダウンに対応可能な情報共有システムを構築する。

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『キャンパス』モデルによる e-Learning の実践 : 早稲田大学人間科学部eスクールの取り組み

西村昭治, 浅田匡, 向後千春, 菊池英明, 金群, 松居辰則, 野嶋栄一郎

日本教育工学会大会講演論文集 20 149 - 152 2004年09月

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早稲田大学eスクールの実践 : 大学教育におけるeラーニングの展望

向後千春, 西村昭治, 浅田匡, 菊池英明, 金群, 野嶋栄一郎

日本教育工学会研究報告集 2004 ( 3 ) 17 - 23 2004年05月

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仮想環境における協調学習のためのデータベースエージェント

金群, 緒方広明, 矢野米雄

全国大会講演論文集 55 ( 3 ) 298 - 299 1997年09月

　概要を見る

通信技術のめざましい発展に伴い, 近年, インターネットを介した仮想コミュニティ, 仮想オフィス, 仮想クラスルームが次々と現われ, このような仮想空間に入り込んで, 仕事したり, 学習したりすることは単なる夢ではなく, 現実のものとなりつつある。MOO (Multi user dimension Object-Oriented)と呼ばれるマルチユーザシミュレーション環境が, こうした仮想空間を容易に実現できるシステムとして注目を集めている。我々はMOOをベースにした協調学習環境の構築を行っている。仮想学習環境の外部にあるデータベースやインターネット上にある豊富な情報資源を教育/学習の教材として活用するため, 外部データベースやWWWサーバなどへのアクセスが必要となる。本研究報告では, それらのアクセスを可能にするエージェントについて述べる。

CiNii J-GLOBAL
仮想コミュニティにおける協調学習支援

邵穎志, 白草義浩, 金群, 矢野米雄

電子情報通信学会技術研究報告. ET, 教育工学 96 ( 578 ) 175 - 180 1997年03月

　概要を見る

仮想コミュニティ環境MOOはネットワークを利用した究極の教育形態であると言われてぃる.しかし,仮想コミュニティ環境MOOを協調学習に利用する際,(1)大容量のデータを取り扱うことが不得意である.(2)インターネットに既存の知識情報を検索・利用することが困難である,という欠点を持っている.そこで,我々は外部テータベースとのリンク,WWWサーバへのアクセスを可能にすることで,これらの問題点を解決し,仮想コミュニティ環境MOOの機能拡張を行った.本稿では仮想コミュニティ環境MOO,MOO環境の問題点と解決方法及び機能拡張されたMOO環境を用いた協調学習支援システムの構築について述べる.

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テキスト型仮想現実システムを利用した協調学習環境

白草義浩, 邵穎志, 金群, 矢野米雄

教育システム情報学会研究報告 1996 ( 2 ) 3 - 8 1996年09月

　概要を見る

資料形態 : テキストデータプレーンテキスト
コレクション : 国立国会図書館デジタルコレクション > デジタル化資料 > 雑誌

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(67)学生による授業評価アンケート : 工学部全学生、全クラスに対する実施と評価(第19セッション教育評価(II))

矢野米雄, 金群, 森吉孝

工学・工業教育研究講演会講演論文集 8 215 - 218 1996年07月

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協調エージェントを用いた人脈活用支援システムの構築

相曽友宏, 郷司敦史, 緒方広明, JIN Q, 矢野米雄, 古郡延子

電子情報通信学会技術研究報告 96 ( 71(OFS96 10-15) ) 31 - 36 1996年05月

　概要を見る

近年のインターネットの普及により, 様々な専門分野の知識を持った人達の潜在的な知識ネットワークが形成されている. 我々は, 知識ネットワークとして人脈を活用し, 問題解決に役立てるためのシステムについて研究を行っている. 人脈を個々の知識を結びつけるネットワークと捉えることにより, 各個人が持つ知識を統合して, より大きな成果を得ることが期待できる. 本稿では, 各個人ごとに人脈の蓄積を行うデータベースPeCo-Collectorと, 人脈を辿り, 協力者を探索するソフトウェアエージェントPeCo-Agentについて述べる.

CiNii J-GLOBAL
外国人のための擬態語・擬音語辞書システムの構築

川崎桂司, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

電子情報通信学会技術研究報告 95 ( 604(ET95 112-131) ) 33 - 40 1996年03月

　概要を見る

本稿では状況.発音.意味.使い方.感覚等に着目した擬態語・擬音語辞書システムJAMIOSについて述べる.日本人は擬態語や擬音語を頻繁に用いる傾向がある.しかしこれらの語は,日本語独特の表現であり感覚的な語なので,日本語を学習する外国人にとって理解が困難である.そこでJAMIOSは,(1)使用する状況をマルチメディア情報を用いて提示し,その状況や発音形態を変化させることで検索が進められる,(2)擬態語・擬音語の特徴に沿った様々な知識や関連語を検索できる,(3)例文を利用して日本語中での使い方を提示する等の特徴を持つ.

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日本語待遇表現学習支援システムの構築

村田利恵, 越智洋司, アヤラヘラルド, 緒方広明, 金群, 矢野米雄, 林敏浩, 野村千惠子, 河野南代子

電子情報通信学会技術研究報告. ET, 教育工学 95 ( 604 ) 41 - 48 1996年03月

　概要を見る

日本語に慣れてきた外国人は,待遇表現の難しさに直面する。例えば日本人と外国人の対人関係の捉え方の違いにより,意思伝達における誤解を生む場合がある.これは待遇表現が,状況や対人関係によって複雑に変化するため,事例的に学習しただけでは対応しきれないことが原因である.我々は外国人が待遇表現を使用したときの問題点が特に,(1)相手が日本でどの対人関係に当たるかわからない.(2)対人関係と状況に適した待遇表現がわからないことにあると考える.本稿ではこれらを考慮した待遇表現学習支援システムの概要について述べる.

CiNii J-GLOBAL
外国人のための擬音語・擬態語辞書システムの構築

川崎桂司, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

教育システム情報学会全国大会講演論文集 20th 225 - 228 1995年08月

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対人関係を考慮した外国人のための敬意表現学習支援システムの構築

村田利恵, 越智洋司, AYALA G, 緒方広明, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子, JIN Q

教育システム情報学会全国大会講演論文集 20th 221 - 224 1995年08月

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外国人のための擬態語・擬音語辞書システムの構築

川崎桂司, 越智洋司, アヤラヘラルド, 緒方広明, 金群, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子

電気関係学会四国支部連合大会講演論文集 1995 332 1995年

J-GLOBAL
人脈活用支援システムにおける人脈探索エージェントのモデル化

緒方広明, 郷司敦史, 金群, 矢野米雄

電気関係学会四国支部連合大会講演論文集 1995 346 1995年

J-GLOBAL
PeCo‐Collector: インタネット環境における人脈データベースシステム

郷司敦史, 緒方広明, 金群, 矢野米雄

電気関係学会四国支部連合大会講演論文集 1995 344 1995年

J-GLOBAL
対人関係を考慮した日本語敬意表現学習支援システムの構築

村田利恵, 越智洋司, アヤラヘラルド, 緒方広明, 金群, 矢野米雄, 林敏浩, 野村千恵子, 河野南代子

電気関係学会四国支部連合大会講演論文集 1995 334 1995年

J-GLOBAL
事例に基づくノウハウの共有システムORMEXの構築

堤清二, 緒方広明, 金群, 矢野米雄

電気関係学会四国支部連合大会講演論文集 1995 340 1995年

J-GLOBAL
柔軟な構造で非定型情報を扱うフレームワーク人脈活用支援システム

古郡延子, JIN Q, 緒方広明, 矢野米雄

システムシンポジウム講演論文集 20th 165 - 168 1994年

J-GLOBAL
人脈活用支援システムの構築 : 個人情報共有活用環境

緒方広明, 森川富昭, 矢野米雄, 古郡延子, 金群

情報処理学会研究報告.IM, [情報メディア] 93 ( 95 ) 29 - 36 1993年10月

　概要を見る

幅広い分野で,かつ多くの人脈を積極的に活用することにより,新しいプロジェクトが生まれたり,商談,企画などのグループ活動が成功したり効率が向上する場合が多い.そこで,本システムはグループ情報源である各個人が所有する人脈をグループで共有活用することを目的とする.本稿では,人脈のように動的で非定型,かつ個人的な情報を共有活用する環境である個人情報共有活用環境について述べる.この環境は,個人レベルでは,データベース,ユーザインタフェイス,検索法において利用者の自由度を高めることにより,個人的で非定型な情報を電子化しやすく,共有レベルでは,システムの使用によりシステムが成長する枠組を持つ.

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人脈活用支援システムの構築

緒方広明, 森川富昭, 林敏浩, 矢野米雄, 土定正明, 古郡延子, 金群

情報処理学会研究報告 93 ( 56(GW-2) ) 57 - 64 1993年06月

　概要を見る

グループの情報源は各個人である．分散オフィス化に伴い，各個人の情報を共有し，それを各分散オフィスで活用できる環境が必要となる．そこで我々は，各個人が人と人との出合によって生じた人脈という情報に着目し，それをグループで共有・活用することを目的とするシステムの構築を行う．これにより，グループ活動の生産性が上がり，組織力が向上すると考えられる．各個人の人脈をグループで活用する場合，各個人が人脈を評価する必要がある．そこで我々は人脈の定量化とその視覚化を行った．本報告では，人脈の考察，人脈の定量化とその視覚化手法，並びに本システムの構成とそれを用いた人脈活用について述べる．It is said that every member of a group is considered as an information source. With the development of distributed offices, we consider the necessity of groupware systems that allow sharing information between each group member for its usage in each distributed office. Therefore we are developing a system whose aim is to share and use the personal connections (PC) that each group member obtains in her/his social relationships. We suppose that in this way our system can raise the productivity and the power of the group in general. When a group member uses other members' PC in the system, s/he has to evaluate the degree of that PC in some way. Therefore the system allows the quantification and visualization of a group PC. In this paper, we describe our considerations about practical use of the PC together with its quantification and visualization methods, the overview of the system and the practical use of the PC provided by this environment.

CiNii J-GLOBAL
エキスパートシステムにおける不確実性を伴った推論およびそのペトリネット表現

金群, 青木敬一

全国大会講演論文集 45 85 - 86 1992年09月

　概要を見る

エキスパートシステムは、知識ベースと推論エンジンを基本構成要素としている。知識ベースを完全に正しい事実とルールで構築するのが理想的である。しかし、現実には、推論中に必要となる事実やルールなどのデータが欠落していたり曖昧であったり、不確実な場合がある。これらに対してもエキスパートシステムは推論が可能でなければならない。ペトリネット(Petri net)は、システムにおける信号あるいは情報の流れを抽象化し簡単に表現できる有効なモデル化技法として知られ、いろいろな分野に適用できる。AI分野では、ルールベースにおける推論、制御ルールの検証、論理プログラムの記述などに適用され効果が得られている。ペトリネットの実行は非決定性を有する。本研究は、ペトリネットのこの特徴を利用し、拡張モデルとして、エキスパートシステムにおいて不確実性を伴った推論を表現しようとするものである。

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確率ペトリネットによるトラップ・システムの挙動解析

金群, 菅澤喜男, 瀬谷浩一郎

全国大会講演論文集 42 345 - 346 1991年02月

　概要を見る

近年、情報システムの大規模化・複雑化が進み、特に分散処理システムにおけるトラップ発生の挙動解析が要望されている。そこで、分散処理形態での親子システムを例として、確率ペトリネットを用いて、トラップ・システムをモデル化し、トラップ発生の挙動解析を行う。

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拡張ペトリネットモデルを利用したバッファの容量の表現

金群, 菅澤喜男, 瀬谷浩一郎

全国大会講演論文集 40 1550 - 1551 1990年03月

　概要を見る

ペトリネット(Petri Net)は、1962年Petri氏の博士論文で最初提出された。その後、研究が活発してきて、新しい概念を導入したいろいろな拡張ぺトリネットを提案されている。その結果、ペトリネットのモデル化能力は一層強化された。本論文では、同時進行並列システムの例として、2台のロボットを持つシステムの性能評価におけるそのシステムにあるバッファの容量に関する表現の方法について考察する。ここでは、拡張ペトリネットモデルとその部分概略到達可能グラフ(APRG:Abstrcted Partial Reachability Graph)により、ペトリネット理論にマルコフ再生過程、待ち行列理論を用いられる方法を提案する。

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https://nislab.human.waseda.ac.jp/
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2025年秋学期
専門ゼミI（情報システム科学）

人間科学部

2025年春学期
情報システム入門

人間科学部

2025年春学期
ヒューマンコンピュータインタラクション

人間科学部

2025年秋学期
卒業研究ゼミ（情報）（情報システム科学）（春）

人間科学部（通信教育課程）

2025年春学期
情報システム入門

人間科学部（通信教育課程）

2025年春学期
専門ゼミ（情報システム科学）（秋）

人間科学部（通信教育課程）

2025年秋学期
専門ゼミ（情報システム科学）（春）

人間科学部（通信教育課程）

2025年春学期
卒業研究ゼミ（情報）（情報システム科学）（秋）

人間科学部（通信教育課程）

2025年秋学期
ネットワーク情報システム学ゼミ（１）　Ｂ

大学院人間科学研究科

2025年秋学期
ネットワーク情報システム学ゼミ（１）　Ａ

大学院人間科学研究科

2025年春学期
ネットワーク情報システム学研究指導　Ｂ

大学院人間科学研究科

2025年秋学期
ネットワーク情報システム学研究指導　Ａ

大学院人間科学研究科

2025年春学期
ネットワーク情報システム学ゼミ（２）　Ａ

大学院人間科学研究科

2025年春学期
ネットワーク情報システム学研究指導（Ｄ）　Ｂ

大学院人間科学研究科

2025年秋学期
ネットワーク情報システム学研究指導（Ｄ）　Ａ

大学院人間科学研究科

2025年春学期
先進ICT技術によるグローカルヘルス課題解決と人間科学に基づく政策形成

大学院人間科学研究科

2025年夏季集中
Contemporary Issues in Human Sciences for Social Innovation in the Global Era

大学院人間科学研究科

2025年秋学期
ヒューマンコンピュータインタラクション特論/Advanced Topics in Human-Computer Interaction

大学院人間科学研究科

2025年秋学期
ネットワーク情報システム学ゼミ（２）　Ｂ

大学院人間科学研究科

2025年秋学期

▼全件表示

特別研究期間制度（学内資金）

利用者中心のネットワーク情報システムにおけるユーザモデルの研究

2012年03月

-

2013年03月

中国中国計量学院、北京大学、上海大学

他学部・他研究科等兼任情報

人間科学学術院大学院人間科学研究科

学内研究所・附属機関兼任歴

2024年

-

2026年

カーボンニュートラル社会研究教育センター兼任センター員

特定課題制度（学内資金）

因果探索によるヘルスデータアナリティクス

2024年

　概要を見る

ヘルスデータ分析による健康リスク評価と予測において、ビッグデータ分析手法により相関関係を明らかにするだけでは十分でない。データにおける潜在的な因果関係を推論し発見する探索的因果分析は有効であると期待されている。しかし、ヘルスデータは多くの要因が複雑に絡み合い、健康に関わる重要な特徴を適切に選択し適用することが容易でないなど多くの課題が残されている。本研究では、人工知能、機械学習、データサイエンス、統計学など分野を横断する学融合的な総合知を創出するConvergentResearchアプローチを用いて、因果探索による新たなヘルスデータアナリティクスの構築を目指して、基盤モデルとアルゴリズムを開発し、有用性と有効性を実験的に検証する。今年度の主な研究成果は以下の通りである。(1)     潜在的な健康リスク要因を特定することは、ヘルスデータ分析における重要な課題である。ニューラルネットワークに基づく多くの分析プロセスは説明可能ではない。分析プロセスを可視化する先行研究があるが、専門家によるドメイン知識が必要となる。本研究では、ドメイン知識に依存せず潜在的健康リスク要因を推定する探索的かつ解釈可能なアプローチを提案し、機械学習による重要な特徴を選択したうえ、因果探索によりリスク要因を発見し、ドメインモデルを構築する。さらに、2つのデータセットを用いて4つのベースラインと比較する評価実験を行った結果、提案するアプローチの有効性を検証している[1]。(2)     多くの特徴選択の手法があるが、本研究では、重み付け総合スコア（WTS）指数を導入し定義し、最適化方策による新たなヘルスデータ因果分析のための複数特徴選択手法を提案し、2つのデータセットを用いて従来の手法より優位な評価結果を得た[2]。さらに、提案手法をウェアラブルデバイスと被験者自己申告から得られたヘルスデータにおける因果関係発見によるライフスタイルと行動の分析に適用し、有用性を確認した[3](3)     人間を理解し健康維持・増進やウェルビーイング追究を支える諸課題と挑戦について検討し、ConvergentResearchによる学融合的な総合知を用いながら、とりわけ、因果探索によるヘルスデータアナリティクスとAIやIoT、ビッグデータなど新興技術との融合による新たな可能性と今後の展開について提示している[4-9]。
"Give-and-Take"に基づく分散データ共有モデルの構築

2023年

　概要を見る

高度デジタル化社会において、増え続けるビッグデータを有効的に利活用するため、データの所有者など利害関係者の利益保護が重要である。本研究は、データ所有者の意志と利益を守りながら、データは分散かつ秘匿状態のまま、利用権を持つ者が信頼して利用できる分散データ共有モデルを新たに提案し構築することが目的である。今年度の研究においては、ギブアンドテイクの考えに基づき、データ所有者と利用者の双方の利益を考慮するデータ共有のインセンティブ手法について検討し、これまでの先行研究で提案してきた利用者個人主導データアクセスコントロール方式及びブロックチェーンと分散型連合学習によるプライバシー保護強化メカニズムとの連携をはかり、実験的な検証を行っている。今年度の主な研究成果は以下の通りである。(1)    技術受容モデル（TAM）の基準に基づきAirbnbを例としてシナリオを設定し、アンケール調査を実施し、集めたデータを分析することにより、行動意図に影響を与える様々な要因を見つけ出し、供給者（提供側）と消費者（利用側）の信頼関係が最も重要な要因であることを明らかにした[1]。(2)     利用者個人主導データアクセスコントロール方式を用いた実験環境のもと、スマートコントラクトによるマルチレジャー協同メカニズムの実験検証[2]及びその結果の分析を行った上、ヘルスデータの統合・共有・分析と分析結果の可視化を検証する実験環境を構築し、適用の可能性と有効性を検討した[3]。(3)     提案モデルを用いてデータ共有と利活用を促進する方策と課題について検討し、ヘルスデータを含むビッグデータ分析により健康など人間が持っている多くの側面を理解し、連合学習やブロックチェーンなど新興技術融合による個人化支援サービスの構築における課題と今後の展開について提示している[4,5]。
ブロックチェーンと連合学習による高信頼データ共有基盤モデルの構築

2022年

　概要を見る

ビッグデータを有効的に利活用するため、セキュリティとプライバシー保護を強化することが不可欠である。本研究では、ブロックチェーンと連合学習を連携させ、データは分散状態のまま維持しつつ、データ所有者があらかじめ設定したポリシーと属性によるアクセス権限に従い、データの中身を明かさずに利用者のリクエストに応じ、データを共有し、利活用することができる高信頼データ共有モデルを新たに提案し構築することを目的とする。今年度においては、データの信頼性保証と取得・共有の効率性を両立する高信頼データアクセスを実現する基盤モデルとメカニズムの構築及び実験検証を行い、研究成果の一部は国際会議や学術論文誌に発表している。
ブロックチェーンを用いた連合学習における個人主導データアクセスコントロール

2022年

　概要を見る

連合学習はデータを集約せずに機械学習モデルを構築できる新たなプライバシー保護技術として注目を集めている。本研究は、データは分散状態のまま維持しつつ、その所有者が予め設定したアクセスポリシーに従い、ブロックチェーンを用いた連合学習における機械学習モデル構築で利用できる新たな個人主導データアクセスコントロール手法を開発することが目的である。今年度の研究においては、Hyperledger Fabricというコンソーシアム型ブロックチェーンと連合学習を連携させたうえ、CP-ABEというポリシーと属性ベース暗号方式による利用者個人主導データアクセスコントロールモデルの構築を試み、研究成果の一部は国際会議や学術論文誌に発表している。
個人モデルに基づくヘルスデータの縦横比較分析

2021年

　概要を見る

ヘルスデータ分析に関するこれまでの研究では、時系列分析や異常検知などに重点を置くばかりで、個人を中心にした比較分析が行われていない。本研究は、過去のデータとの比較分析のみならず、同年代あるいは似た生活習慣など類似性を有する他の個人またはグループとの比較分析を行うため、個人モデルに基づくヘルスデータの縦横比較分析手法を新たに提案し、計算論的な方法論として構築し確立することが目的である。今年度の研究においては、常に更新するヘルスデータに適合する動的な特性を考慮した提案手法を実現するための基盤モデル構築とアルゴリズムを考案し検証を行っている。研究成果の一部は国際会議や学術論文誌に発表している。
個人モデルに基づく個に適応するヘルスデータの比較分析法

2021年

　概要を見る

近年、ウェアラブルデバイスやセンサーにより歩数、睡眠などの活動量・生活データ、血圧、心拍などの健康関連データを含む個人に関わるパーソナルデータが持続的に収集し蓄積することが可能となった。本研究では、パーソナルデータを分析することにより個人モデルを構築し、それに基づきヘルスデータを比較しながら分析する、個に適応する新たな手法を提案し確立することを目的とする。具体的には、ヘルスデータを収集し、個人の現在のデータと過去のデータを比較分析するとともに、年齢や生活習慣など何らかの類似性を有する他の個人またはグループとの比較分析を行う検証実験を行った。研究成果の一部は国際会議や学術論文誌に発表している。
パーソナルアナリティクスによる個人化ヘルスケアのモデル構築

2021年

　概要を見る

本研究は、パーソナルデータ分析に基づき個に適するヘルスケアについて探究し、モデルを構築することが目的である。具体的には、ビッグデータと人工知能技術を用いて、ウェアラブルデバイスやセンサーで収集・蓄積される歩数、睡眠などの活動量・生活データ、血圧、心拍などの健康関連データを含む個人に関わるパーソナルデータを分析することにより個人モデルを構築するパーソナルアナリティクス手法を新たに提案する。今年度の研究においては、これまでの研究で提案している個人モデルの考えに基づき、個々の年齢、生活スタイルや健康状態に適する個人化ヘルスケアモデルの構築を試み、研究成果の一部は国際会議や学術論文誌に発表している。
ブロックチェーンを用いたパーソナルデータのプライバシー保護と利活用基盤モデル構築

2020年

　概要を見る

本研究は、パーソナルデータ利活用におけるプライバシー保護を強化するため、ブロックチェーン技術を用いてデータのオーナー（所有者）が主導でデータへのアクセスコントロールを可能とする安全性の高いプラットフォームを提案することが目的である。今年度の研究においては、データが時系列的に分散保持され、記録されたデータが改竄不可能といった高い信頼性が確保できるブロックチェーンの分散台帳機能を活かしながら、ハッシュや暗号化技術を利用したデータのオフチェーン保存など、個人主導によるデータアクセスコントルールを基本とする新たなフレームワークを提案し、検証を行った。研究成果の一部は国際会議や学術論文誌に発表している。
パーソナルデータ分析に基づく統合個人モデルの構築

2018年

　概要を見る

本研究は、特定のシステムに依存せず、複数の異なるシステムを跨り適用可能な個人モデルを提案し、パーソナルデータの特性を考慮しながらデータ分析に基づく統合個人モデル（UnifiedIndividual Model）の構築法を計算論的な方法論として開発し確立することが目的である。具体的には、ヘルスケアやソーシャルメディアにおけるパーソナルデータを実験データとして取得し、ブロックチェーンを利用したパーソナルデータにおけるプライバシー保護の強化をはかる仕組みづくりや関連基盤アルゴリズムの開発を行い、検証・評価実験を実施する。さらに、実験結果を分析し、今後の展開と応用の可能性と課題について検討する。
パーソナルデータ分析による個人モデルの構築法

2017年

　概要を見る

　本研究ではパーソナルビッグデータに基づくパーソナルアナリティックス（PersonalAnalytics）を新たに提案し、個人モデル（IndividualModel）を構築するための動的分割統治法を計算論的な方法論として研究開発するとともに、実験用データを収集し、検証実験を行い、結果を分析する。本研究は、パーソナルビッグデータの特性を考慮した動的分割統治法をコアに、「分人」という概念を導入した個人中心の統合モデリング手法（UnifiedIndividual Modeling）を新たに提案し確立することを目指すものである。また、本研究で提案している個人モデルは、従来のユーザモデルと違って、特定のシステムに依存しないものであり、それによりシステムをまたがる個別化サービスを提供すことが可能となる。
マイクロコンテンツを有効利用するためのソーシャルラーニング基盤モデルの構築

2016年武　博

　概要を見る

In this study, we propose a fundamentalmodel for social learning in order to effectively use micro contents aseducational resources, based on personal data analytics and individualmodeling. We improve data-driven individual modeling, proposed in our previousstudy, by introducing the concept of dividual and divide-and-conquer algorithm.We further propose a temporal social network analysis approach for dynamiccommunity mining and tracking, and develop overlap community detectionalgorithm by spectral clustering based on node convergence degree that takesboth the network structure and node attributes into account. We use topicevolution model and temporal social network analysis for topic tracking andassessing and pattern extraction as well. Experiments have been conducted basedon different data sets, and comparison with related works and result analysis haveshown the effectiveness of our proposed model and approach.
学習プロセスを手助けするためのソーシャルラーニング基盤モデルの構築と実証実験

2015年

　概要を見る

本研究では、ソーシャルラーニングを、授業や研修、個人の読書、他人との情報共有やインタラクション、日々の生活や社会活動、仕事経験といった知識獲得プロセスを包括的かつ有機的に融合し、一種の拡張されたラーニングプロセスとしてとらえ、基盤モデルを構築する。さらに、利用者の情報アクセス履歴や学習活動を含むパーソナルデータを分析・マイニングすることにより、適応型学習支援を可能とする利用者の個人モデルを構築し、ソーシャルラーニングにおける学習プロセスを手助けするための支援メカニズムを開発し、実験的な試作と検証を行っている。
個人ビッグデータの持続的活用を実現するための基盤モデルとメカニズムの研究開発

2014年

　概要を見る

本研究では、個人に関わる日々の情報行動や情報アクセス履歴を記録するライフログをパーソナルデータと呼び、長期間にわたり蓄積されたパーソナルデータを一種の個人ビッグデータととらえる。このような個人ビッグデータを持続的、効果的に活用するための基盤モデルを提案し、多種多様なデータを集約し、組織化するメカニズムおよび、個人化サービスを提供するためのユニファイド・インディビジュアル・モデリング手法を研究開発している。さらに、SNS環境における動的ユーザプロファイリング、ソーシャルデータ分析によるグループにおける個人の役割の特定、ソーシャルラーニングにおける学習行動分析などへの適用を試みた。
適応型ラーニングサービスを提供するための統合ユーザモデルと基盤メカニズムの研究

2013年周　暁康

　概要を見る

本研究では、ソーシャルネットワーキング環境における利用者の情報アクセス行動履歴やログデータなどを解析し、利用者と情報環境両方の複合要素を考慮したユニファイドユーザモデリング手法を提案し、統合ユーザモデルを構築するとともに、適応型ラーニングサービスを提供するための基盤メカニズムおよび関連アルゴリズムを研究開発する。本年度では、・これまで提案している「進化する統合情報環境の基盤モデル」をベースに、ライフログのような個人ビッグデータを利活用するためのモデル改善と拡張を行い、データ整合、情報融合、再利用可能な知識化を行うとともに、個人ビッグデータに基づくアプリケーションに依存しないユニバーサルユーザモデルを構築する手法を提案している。・TwitterのようなSNS環境における利用者のメッセージやり取りやフォロー関係などから社会的役割と関係ネットワークを推定し、利用者参加型の情報検索・推薦メカニズムを考案するとともに、社会的役割に関わるさまざまな属性やSNS環境および実世界におけるさまざまな状況とコンテキストを総合的に考慮し、マッピングをすることにより社会的役割の特定を図り、基本モデルの構築及び必要なアルゴリズムの開発を行っている。・これまで提案しているDynamical Socialized User Networkingモデルに基づいて、ソーシャルネットワーキング環境における利用者の多次元属性データを解析することによる動的ユーザプロファイリング手法を提案し、中心性指数をベースにした複数のメジャーを新たに定義し導入することによって、ソーシャルネットワーキングにおける利用者個人の重要度と貢献度の定量化を図り、実験データを用いた実験評価を行っている。・ソーシャルネットワーキング環境における利用者のニーズに適合したデータの集約と整合を実現するため、これまで提案しているOrganic Streamsメタファーの改善と拡張を行い、Twitterから取得したデータを用いた評価実験を行っている。また、Eye-Trackingを用いたソーシャルメディアにおける閲覧パターン抽出法を考案し、評価実験を行った。・タスク指向ラーニングプロセスにおけるアクションパタンを発見するアルゴリズムを考案し、ゴール駆動ラーニンググループの動的構成及びそれに基づく適応型ラーニングコンテンツの推薦サービスを実現するためのメカニズムを開発し、プロトタイプシステムを用いて実験評価を行っている。・関連の研究成果をまとめた研究論文を発表している。
利用者と情報環境の統合モデリングによる適用型学習支援メカニズムの研究開発

2012年

　概要を見る

　本研究では、「ユーザ中心」の理念に基づき、クラウド環境における利用者の情報アクセス行動や学習活動を解析し、利用者と情報環境の状況やコンテキストを考慮した統合モデリング手法を提案し、基盤モデルを構築するとともに、利用者のニーズに適合した利用者主導の適応型学習支援メカニズムおよび関連のアルゴリズムを研究開発する。本年度では、・クラウド環境における利用者の情報アクセス行動や学習活動を解析し、利用者と情報環境の状況やコンテキストを考慮した統合モデリングを実現するための統合情報環境のフレームワークを提案し、それに基づき、利用者の利便性とシステムの柔軟性を両立させるスケーラブルなサービス指向でありながら、ユーザモデルに基づく個人に適応する学習統合支援環境の基盤モデルを構築している。・利用者の情報アクセス行動または学習活動からユーザコンテキストをキャプチャーし、ユーザモデルを動的に作成する手法を提案している。・これまで提案している利用者とシステムのインタラクションに基づく逐次適応モデルと、新たに開発した挙動解析に基づく最適化プロセス推薦モデルを統合し、それに基づく目的駆動型学習プロセスナビゲーションシステムを構築している。・利用者の個性を重視しながら利用者間の共通性をも考慮し、利用者の興味とニーズや情報アクセスの変化などを適時に検知するアルゴリズムや、利用者の情報アクセス挙動をパターン化し、挙動パターンの類似度によって過去の成功した学習プロセスを抽出するアルゴリズムを考案し、目標学習者にとって最適化された学習プロセスを推薦する仕組みを開発し、適応型個人化学習サービスとして提供するプロトタイプシステムを構築し、実験的な評価を行っている。・TwitterやFacebookといったソーシャルメディアにおける大量に生成された非構造化ストリームデータ（ソーシャルストリーム）を有機的・効果的な利用が可能な知識情報コンテンツとして組織化するためのアルゴリズムを開発し、プロトタイプシステムを構築し、実験的な評価を行っている。・関連の研究成果をまとめた研究論文を発表している。
クラウド環境における適応型学習統合支援メカニズムの開発と実証実験システムの構築

2011年

　概要を見る

　近年、ソーシャルコンピューティングやライフログが声高に叫ばれ、クラウドサービスをはじめとするサービス・コンピューティングの研究や利活用が盛んに行われている。その一方、情報通信技術を活用したｅ－ラーニングは、何時でも何処でも求められる教育が手に入る技術として、研究開発が盛んに行われ、広く活用されている。クラウドサービスを利用した教育・学習資源とデジタルコンテンツの共有活用は、高等教育機関のみならず、社会人を対象とする職業訓練や特殊技能の習得、在職研修など企業や一般社会でも可能となり、持続発展可能な生涯学習社会の実現に向けて重要な意味をもつと考えられる。しかし、従来の多くのｅ－ラーニング支援システムは、先進な技術を利用した高度な機能の取り入れに重点を置く一方、各学習者のバックグランドや学習能力、現在の学習環境など個人的な特性といった人間的な側面はあまり考慮されていない。学習者は与えられたシステムと機能しか利用できなく、受動的に進めざるを得なかった。　そこで、本研究では、「ユーザ中心」の理念に基づき、クラウド環境における利用者の情報アクセス行動や学習活動を解析して、それに基づくラーニングオブジェクトのネットワークモデルを構築するとともに、利用者のニーズに適合した学習コンテンツをサービスとして提供する利用者主導の適応型学習統合支援システムを提案し、プロトタイプシステムを構築し、評価実験を行う。本年度では、　・利用者の情報アクセス行動や学習活動をソーシャルネットワーク分析手法によりマイニングし、ラーニングオブジェクトの内側の属性と他のラーニングオブジェクトとの関連性や利用者の関係やソーシャル的な要素を複合的に考慮したネットワークモデルを提案している。　・ソーシャルメディアから続々と大量に生成された構造化されていないデータに対応するため、これまで提案してきたユビキタス・パーソナル・スタディ（Ubiquitous Personal Study、略してUPS）を拡張し、ソーシャライズドUPS（Socialized Ubiquitous Personal Study、略してS- UPS）フレームワークを提案し、クラウド環境をベースにした試作システムを構築している。　・マイクロブロックサービスとS- UPS試作システムを統合し、ブレンディッドラーニング支援環境として実験的に試用し、実験評価を行っている。　・関連の研究成果をまとめた研究論文を発表している。
何時でも何処でも手軽に使える利用者主導のサービス指向学習支援環境の構築と実証実験

2008年シュティフ　ロマン

　概要を見る

　近年、所謂Web 2.0が声高に叫ばれ、Webサービスをはじめとするサービス・コンピューティングの研究が盛んに行われている。本研究では、人間がテクノロジに迎合するのではなく、テクノロジが人間に適合するという「人間中心」の理念に基づき、サービス・コンピューティング技術を利用して、何時でも何処でも手軽に使える利用者主導のサービス指向学習支援環境を提案し、その基盤モデルを構築するとともに、初歩的な実証実験を行うものである。　これまで、個人の情報アクセスとコンテンツ共有を統合管理するメタファーとしてUPS (Ubiquitous Personal Study、ユビキタス個人書斎)およびそれを支援するためのフレームワークを提案している。本年度では、さらに、ユーザプロファイリングやコンテキストアウェアネス技術を活用し、システムが利用者に適合するメカニズムの開発および、Webサービスのマッシュアップによるプロトタイプシステムの試作を行っている。また、利用者のさまざまな情報探索行動からユーザコンテキストをキャプチャーすることにより動的ユーザモデルを構築し、それに基づき、人間のニーズにより適合した、何時でも何処でも手軽に使える利用者主導のサービスを提供するFlowable Service Modelを提案し、関連の研究成果をまとめた研究論文を発表している。
人間中心のユニバーサル・ユビキタス情報アクセス共有活用支援環境の構築

2007年シュティフ　ロマン

　概要を見る

　情報通信技術（ＩＣＴ）の急速な進歩に伴い、何時でも何処でも誰でも使えるユビキタスネットワーク社会のインフラが整いつつある。このような社会であらゆる人がＩＣＴの恩恵を実感でき、安心して快適で便利な生活をしていくためには、誰もが時間的、空間的、身体的制約、知識、言語の壁を超えて、手軽に使いこなせる情報環境やユーザーインターフェースが必要不可欠である。本研究では、ユビキタス環境において、ライフタイムにわたる情報アクセス共有活用のあり方について検討し、それを支援するシステムを実現するための主な問題と課題を明らかにし、人間を中心に据えたアプローチと関連技術を研究開発し、ロングタームにわたるユビキタス情報アクセス・マネジメント・共有活用支援環境を構築し、実証実験を行うことを目指している。　本年度では、まず、共有・共同利用を念頭に、ロングタームにわたるユニバーサル・ユビキタス情報アクセス共有活用支援環境を実現するために、利用者の利便性とシステムの柔軟性やスケーラビリティの両立を可能とする人間中心のサービス指向アプローチについてサーベイや研究調査を行った。また、利用者の情報アクセス行動を推定する逐次適応モデルなどを提案し、人間の情報行動をモデル化するとともに、情報探索・推薦、情報アクセス・一括管理、共有活用を支援するプロトタイプシステムとして、BESS（Better Search and Sharing、「よりよい検索・共有」）やUPS（Ubiquitous Personal Study、「ユビキタス・パーソナル・スタディ」）、モバイル検索のためのスクロールなしのインタフェースなどを研究開発し、実験評価を行っている。
サービス指向ユビキタス・ラーニング支援環境の構築と実証実験

2007年シュティフ　ロマン

　概要を見る

　近年、Webサービスをはじめとするサービス・コンピューティングの研究が盛んに行われ、新たな学際的な研究分野としてサービス科学を提唱されている。本研究は、利用者主導のサービス指向ユビキタス・ラーニング支援システムを提案し構築するとともに、多様な利用者の異なる個性、能力、ニーズなどに柔軟に対応でき、現在普及しつつあるブロードバンドネットワーク環境を生かした高度な機能を研究開発することを目指すものである。本研究でいうサービスは、狭義的なｅ－サービス（Webサービス）やｕ－サービス（ユビキタス・サービス）にとどまらず、利用者の利便性とシステムの柔軟性やスケーラビリティを両立させた広義的なｕ－サービス（ユニバーサル・サービス）をめざすものである。サービスは、コンピュータやネットワークを人間に奉仕させるものだと位置づけるものである。　本年度では、デジタルキャンパスとフィジカルキャンパスとのシームレスな融合をめざす「成長するキャンパス（Growing Campus）」の理念のもと、利用者主導のユビキタス・ラーニングを支援するサービス指向モデルを提案し、さらに、実証環境システムのプロトタイプとして、ユビキタス・パーソナル・スタディ（Ubiquitous Personal Study、略してUPS）というメタファーを提案している。UPSは、個人のためにすべての情報・情報アクセスを一括管理・組織化するとともに、個人ポータルとして情報のアクセス共有活用を支援する統合環境を提供するものであり、一種の個人化されたデジタル仮想書斎である。個々に分散したUPS はさらにクロースSNS（Cross Social Networking Service、略してXSNS）を通して相互連結により友人関係を確立し、情報共有、情報推薦、友人推薦などの機能を提供する基盤プラットフォームとなる。UPSは、WEBサービスのマッシュアップによるシステムの試作を行い、実験評価を進めている。
学習者と学習環境のインタラクションをさりげなく支援する知能情報メディアの研究

2005年

　概要を見る

　従来の多くのｅ－ラーニングシステムは、人間的な部分が抜け落ちた、単なる知識や情報の伝達でしかない。ラーニングコミュニティなど知識情報共有型ｅ－ラーニングシステムにおいて、学習コンテンツの作成・流通・再利用における統一規格や、異なるシステム間の互換性など多くの問題点と課題が残されている。本研究は、それらの問題を総合的に解決することを目指して、学習者と学習環境のインタラクションをさりげなく支援するとともに、人間とのインタラクションを通じて進化する知能情報メディアを提案し、モデル化とそのあり方について探求し明らかにするものである。　本年度では、これまでの研究において提案されている「社会的インタラクション支援フレームワーク」に基づき、知能情報メディアの基本モデルの洗練化をはかり、そのうえ、学習者間の社会的相互作用を促進するとともに、学習者と学習環境のインタラクションを支援する仕組みを考案し、サービス指向ユビキタス・ラーニング支援やスケーラブルな情報共有システムなどの実証環境の構築への適用を試みた。さらに、オントロジに基づくコンテキスト・アウェア・モデルを提案し、人間と情報環境のインタラクションをさりげなく支援することが可能な能動的な知能情報メディアへの展開の可能性について検討した。
利用者主導の知識情報共有型ｅ－ラーニング支援環境の研究開発

2005年

　概要を見る

　情報通信技術を活用したｅーラーニングは、いつでもどこでも求める教育が手に入るシステムとして、盛んに研究開発が行われ、活用されている。しかし、ｅ－ラーニングを含めて一般的に自己学習は、学習者が孤独感に陥ったり、学習ペースがつかめず脱落したり、学習者の意欲や教育効果を殺ぐなど、挫折するケースが見受けられる。本研究は、ピア・ツー・ピア（P2P）ネットワーク技術を利用して、利用者主導の知識情報共有型ｅ－ラーニング支援システムを提案し、多様な利用者の異なる個性、能力、ニーズなどに柔軟に対応できる高度な機能を研究開発するとともに、教育／学習現場において評価実験を行いながら、問題点を明らかにし、改良を加え、その有効性を実証し、そのうえ、新たな知識情報共有型ｅ－ラーニング支援環境を構築するものである。　本年度では、従来のクライアント／サーバモデルに基づいたｅ－ラーニング・モデルと比較しながら、P2Pネットワークの特徴を生かした学習モデルおよび学習者個人のニーズや能力に柔軟に対応できる利用者主導のｅ－ラーニング支援仕組みを考案するとともに、これまでの研究において提案されている「社会的インタラクション支援フレームワーク」を発展させ、サービス指向ユビキタス・ラーニング支援環境を提案し、プロトタイプシステムの構築を行った。さらに、分散型P2P ネットワークと集中型個人・グループ・メディア・ツールの統合によるスケーラブルな知識情報共有システムを提案し、その試作を進んでいる。
学習者と学習環境のインタラクションをさりげなく支援する知能情報メディアの研究

2004年

　概要を見る

　協調学習に基づくコミュニティ型ｅ－ラーニングシステムでは、学習者の自発的な参加および知識情報の共有が奨励される。実践において、こういった学習者主導型ｅ－ラーニングの難しさの１つとして、仮想環境におけるコミュニケーションとインタラクションにあると指摘されている。本研究は、学習者と学習環境のインタラクションをさりげなく支援するとともに、人間とのインタラクションを通じて進化する知能情報メディアを提案するものである。　本年度では、これまでの研究において提案されている仮想環境メディアの考え方を発展させ、知能情報メディアの基本要件を検討し、モデル化を試みるとともに、知能情報メディアモデルのコアとなる「社会的インタラクション支援フレームワーク」を考案した。また、利用者の個性の差異を超えて、相互理解を促進する仕組みを有し、人間とのインタラクションを通じて進化させるために、知能情報メディアに「暗黙の知」を用いた支援メカニズムを埋め込み、学習環境とコンテンツとのシームレスな統合をはかり、学習者同士間のコミュニケーション、学習者と学習環境やコンテンツとのインタラクションをさりげなく支援する手法を提案している。このような「支援メカニズム」を実現するためには、（１）人間の会話や挙動を観察し、人間とのインタラクションを通じて人間の意図を理解できる知的エージェント技術、（２）多様なデータと知識を統一規格で記述できるXML およびそれを発展させた技術、（３）利用者間のダイレクトなコミュニケーションと情報交換や、対等な知識共有と効率的な配送仕組みを提供できるピア・ツー・ピア（P2P）ネットワーク技術、を融合したアプローチを考案し、本年度では、「社会的インタラクション支援フレームワーク」に基づき、ユビキタスラーニングを実現するためのP2P型プロトタイプシステムを構築し、初歩的な実験を行った。
ピア・ツー・ピア技術を活用したラーニングコミュニティの研究

2003年

　概要を見る

　高度情報ネットワーク化社会において、知識の更新のペースがますます速めており、従来の学校、大学での教育では対応できなくなりつつある。そのため、生涯を通じた多様な学習者を対象とする教育／学習システムが求められている。　本研究は、ピア・ツー・ピア（P2P）技術を利用して、多様な学習者に対して広く開かれた新たなコミュニティ型ｅーラーニングシステムを提案することを目的とする。本年度では、学習者個々のニーズに柔軟に対応できるパーソン・ツー・パーソンｅーラーニングモデルを新たに考案し、P2Pネットワークの特徴を生かした教授／学習支援環境のあり方について検討するとともに、従来のクライアント／サーバモデルに基づいたｅーラーニングモデルとの比較を行った。また、ｅーラーニングに適したP2P技術とは何かについて、サーベイを行い、ラーニングコミュニティの特徴を発揮でき、従来のｅーラーニングシステムにおける学習者個性の喪失や孤独感、学習ペースがつかめにくいなどの問題を改善し、ｅーラーニングに適したP2P仕組みの提案を行った。それをもとに、ピア・ツー・ピア型ラーニングコミュニティにおけるコミュニケーションやコラボレーションを支援し、学習者個人のニーズや能力に応じた学習内容や進み方を設定可能な支援環境とグループウェアツールを設計し、試作を行った。さらに、ピア・ツー・ピア型ラーニングコミュニティを利用するためのクライアントシステムとGUIインターフェースをも試作し、初歩的な実験評価を行い、これからの改良・改善策をまとめた。　従来の多くのｅーラーニングシステムは、人間的な部分が抜け落ちた、単なる情報や知識の伝達でしかない。本研究は、P2P技術の利点とラーニングコミュニティの特徴を発揮し、融合することによって、ピア・ツー・ピアｅーラーニングに適した学習モデルと仕組みづくりを探求し、従来のｅーラーニングにおける問題点を解決し、改善するものである。

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