Updated on 2022/05/17

写真a

 
JIN, Qun
 
Affiliation
Faculty of Human Sciences, School of Human Sciences
Job title
Professor
Profile

Qun Jin is a professor at the Networked Information Systems Laboratory, 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 technologies. His recent research interests cover computing for human well-being, behavior and cognitive informatics, big data, personal analytics and individual modeling, health analytics, learning analytics, cyber security, blockchain, artificial intelligence, and applications in healthcare and learning support. He is a senior member of Association of Computing Machinery (ACM), Institute of Electrical and Electronics Engineers (IEEE), and Information Processing Society of Japan (IPSJ). He is a foreign member of the Engineering Academy of Japan (EAJ).

Concurrent Post

  • Faculty of Human Sciences   Graduate School of Human Sciences

Degree

  • Ph.D

Research Experience

  • 2003.04
    -
    Now

    Waseda University   Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences   Professor

  • 2018.09
    -
    2020.09

    Waseda University   Faculty of Human Sciences   Deputy Dean (International Affairs)

  • 2018.09
    -
    2020.09

    Waseda University   Graduate School of Human Sciences   Dean

  • 2014.09
    -
    2016.09

    Waseda University   Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences   Chair

  • 1999.04
    -
    2003.03

    University of Aizu   School of Computer Science and Engineering   Associate Professor

  • 1995.04
    -
    1999.03

    Tokushima University   Department of Information Science and Intelligent Systems, Faculty of Engineering   Associate Professor

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Professional Memberships

  •  
     
     

    ACM

  •  
     
     

    IEEE Computer Society

  •  
     
     

    IEEE

  •  
     
     

    THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE

  •  
     
     

    INFORMATION PROCESSING SOCIETY OF JAPAN

  •  
     
     

    The Engineering Academy of Japan (EAJ)

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    CCF

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Research Areas

  • Learning support system   Personalized learning support, Learning analytics

  • Intelligent informatics   Artificial intelligence, Intelligence computing

  • Life, health and medical informatics   Smart health, AI-enhanced personalized healthcare

  • Educational technology   e-learning support

  • Web informatics and service informatics   Human informatics, Computing for well-being

  • Cognitive science   Behavior and cognitive informatics, Individual modeling

  • Database   Big data, Personal data analytics

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Research Interests

  • learning analytics and support

  • smart health and computing for well-being

  • AI-enhanced personalized services

  • cyber security

  • blockchain

  • intelligence computing

  • data quality assurance and sustainable use

  • personal analytics and individual modeling

  • big data

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Papers

  • 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  2021.08  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    DOI

  • 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  2021.05  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    DOI

  • 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  [Refereed]  [International coauthorship]

    DOI

  • 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     1 - 9  2021  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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     1 - 1  2021  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2021.01  [Refereed]  [International journal]

    Authorship:Lead author, Last author

    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  2020.10  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author, Corresponding author

    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  2020.08  [Refereed]  [International journal]  [International coauthorship]

    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  2020.07  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2020.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2020.04  [Refereed]  [International journal]

    Authorship:Last author, Corresponding author

    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  2020.02  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    DOI

  • Detection of Health Abnormality Considering Latent Factors Inducing a Disease

    Kiichi Tago, Kosuke Takagi, Qun Jin

    IEEE Access   8   139433 - 139443  2020  [Refereed]  [International journal]

    Authorship:Last author, Corresponding author

    DOI

  • 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    2019.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author, Corresponding author

    DOI

  • 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  2019.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author, Corresponding author

    DOI

  • 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  2019.03  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    DOI

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

    Weimin Li, Xiaokang Zhou, Shohei Shimizu, Mingjun Xin, Jiulei Jiang, Honghao Gao, Qun Jin

    IEEE Access   7   45451 - 45459  2019  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author, Corresponding author

    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  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Corresponding author

    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  2018.12  [Refereed]  [International journal]  [International coauthorship]

    DOI

  • 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  2018.12  [Refereed]  [International journal]

    DOI

  • 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  2018.10  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author

    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  2017.12  [Refereed]

     View Summary

    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  2017.10  [Refereed]

  • 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  2017.03  [Refereed]

     View Summary

    With the popularity of social networking services (SNSs) and the increase of users, individuals' social roles in a social network have become more and more important in terms of the recommendation of personalized services and the collective decision-making process. Usually, 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 paper, we focus on analyzing and identifying users' dynamical social roles to facilitate the collective decision-making process. After introducing the social choice theory and an improved collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way and develop an integrated mechanism to utilize the identification of social roles to support the collective decision making. Based on a developed NetLogo-based tool, a case study for the course-offering determination with an application scenario is demonstrated to show the process of using users' social roles to support the collective decision making. The comparison experiment conducted between our method and the Delphi method shows the usefulness of our proposed method to help users achieve the decision consensus in a more efficient way.

    DOI

  • Enabling the Social Internet of Things and Social Cloud Introduction

    Weishan Zhang, Qun Jin, Didier El Baz

    IEEE CLOUD COMPUTING   2 ( 6 ) 6 - 9  2015.11  [Refereed]

     View Summary

    The social Internet of Things and social cloud have the potential to move forward hand in hand, changing our social patterns and providing new ways to communicate and collaborate.

    DOI

  • 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  2014.07  [Refereed]

     View Summary

    With the high development of social networks, collaborations in a socialized web-based learning environment has become increasing important, which means people can learn through interactions and collaborations in communities across social networks. In this study, in order to support the enhanced collaborative learning, two important factors, user behavior patterns and user correlations, are taken into account to facilitate the information and knowledge sharing in a task-oriented learning process. Following a hierarchical graph model for enhanced collaborative learning within a task-oriented learning process, which describes relations of learning actions, activities, sub-tasks and tasks in communities, the learning action pattern and Goal-driven Learning Group, as well as their formal definitions and related algorithms, are introduced to extract and analyze users' learning behaviors in both personal and cooperative ways. In addition, a User Networking Model, which is used to represent the dynamical user relationships, is proposed to calculate user correlations in accordance with their interactions in a social community. Based on these, an integrated mechanism is developed to utilize both user behavior patterns and user correlations for the recommendation of individualized learning actions. The system architecture is described finally, and the experiment results are presented and discussed to demonstrate the practicability and usefulness of our methods.

    DOI

  • 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  2014.02  [Refereed]

     View Summary

    Services are expected to be a promising way for people to use information and computing resources in our emerging ubiquitous network society and cloud computing environments. In this study, we propose a metaphoric concept called a flowable service. It is defined as a logical stream that organizes and provides circumjacent services in such a way that they are perceived by individuals to be naturally embedded in their surrounding environments. We present our view on how some of these problems, such as the flexibility, portability and interoperability of services, can be solved using flowable services in order to provide a seamless integration of diverse services in the most intuitive "flowable" way possible, thus achieving maximum satisfaction for both service providers and consumers while decreasing the delivery cost of the services. Recognizing the importance of the awareness of each individual's context for a smooth and accurate provision of services, we further propose a human-centric framework for context-aware flowable services, which harnesses the users' contexts to enable a pro-active support of human activities in a flexible and natural way. Owing to context-awareness, this framework can find and integrate circumjacent services that are considered needed by each individual and can create an ambient service environment that is tailored to his/her specific needs, proclivities and characteristics. (C) 2012 Elsevier Inc. All rights reserved.

    DOI

  • 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 )  2013.03  [Refereed]

     View Summary

    Sharing resources and information on the Internet has become an important activity for education. In distance learning, instructors can benefit from resources, also known as Learning Objects (LOs), to create plenteous materials for specific learning purposes. Our repository (called the MINE Registry) has been developed for storing and sharing learning objects, around 22,000 in total, in the past few years. To enhance reusability, one significant concept named Reusability Tree was implemented to trace the process of changes. Also, weighting and ranking metrics have been proposed to enhance the searchability in the repository. Following the successful implementation, this study goes further to investigate the relationships between LOs from a perspective of social networks. The LONET (Learning Object Network), as an extension of Reusability Tree, is newly proposed and constructed to clarify the vague reuse scenario in the past, and to summarize collaborative intelligence through past interactive usage experiences. We define a social structure in our repository based on past usage experiences from instructors, by proposing a set of metrics to evaluate the interdependency such as prerequisites and references. 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 in our repository. The algorithm generates adaptive routes, based on past usage experiences, by computing possible interactive input, such as search criteria and feedback from instructors, and assists them in generating specific lectures.

    DOI

  • 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  2010.07  [Refereed]

     View Summary

    In line with the popularity of the 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. In distance learning (or e-learning), SCORM provides an efficient metadata definition for learning objects to be searched and shared. To facilitate searching in a federated repository, CORDRA provides a common architecture for discovering and sharing Learning Objects. 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 enhance CORDRA. We further collect relevant information, while users are utilizing Learning Objects, such as citations and time period persisted. The feedbacks from the user community are also considered as critical elements for evaluating significance degree of Learning Objects. Through theses factors, we propose a mechanism to weight and rank Learning Objects in the MINE Registry, in addition to other external learning objects repositories. As a practical contribution, we provide a tool called "Search Guider" to assist users in finding relevant information in Learning Objects based on individual requirements.

    DOI

  • Design of a virtual community based interactive learning environment

    Q Jin

    INFORMATION SCIENCES   140 ( 1-2 ) 171 - 191  2002.01  [Refereed]  [International journal]

    Authorship:Lead author, Corresponding author

     View Summary

    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

  • 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  2021.06  [Refereed]  [International journal]  [International coauthorship]

    Authorship:Last author, Corresponding author

    DOI

  • 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  2021.02  [Refereed]  [International journal]

    Authorship:Last author, Corresponding author

    DOI

  • 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 )  2020.12

     View Summary

    <title>Abstract</title>A color is a powerful tool used to attract people’s attention and to entice them to purchase a product. However, the way in which a specific color influences people’s color selection and the role of their eye movements and cultural factors in this process remain unknown. In this study, to delve into this problem, we designed an experiment to determine the influence of specific colors on people’s product preferences by using an eye-tracking device, intending to identify the role of their eye movements and cultural factors. Based on the experimental data, a detailed influence path model was built to describe the effect of specific colors on product evaluations by an integrated moderation and mediation analysis. Our findings show that in the influence process, the effects of specific colors on product evaluations are mediated by eye movements. Additionally, cultural factors partly moderate the process as an influencing factor. The research findings from this study have important implications for user-centered product design and visual marketing management.

    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  2020.10  [Invited]  [International journal]  [International coauthorship]

    Authorship:Last author

    DOI

  • 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

    DOI

  • 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)    2019.12  [Refereed]

    Authorship:Last author, Corresponding author

     View Summary

    (accepted)

  • Culture-based Color Influence Paths Analysis by Using Eye-tracking Devices

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

    Proc.CyberSciTech2019 (IEEE Cyber Science and Technology), Fukuoka, Japan    2019.08  [Refereed]  [International coauthorship]

    Authorship:Last author

  • 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  2019.07  [Refereed]

  • 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  2019.07  [Refereed]

    DOI

  • 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  2019.07  [Refereed]

    DOI

  • 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    2019.04  [Refereed]

  • 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  2019.04  [Refereed]

     View Summary

    © 2019 Elsevier GmbH Introduction: The utilization of information and communications technology (ICT) devices is a new way to record and analyze health data of the elderly. This time-series study aimed to analyze health changes, and the correlation between pulse manifestation and health indicators, in the elderly. Methods: We conducted continuous 93-day monitoring of health data and pulse records in 8 elderly participants. A time series method was used to analyze health changes in participants. The correlation between pulse manifestation and health indicators was analyzed using a structural equation model. Results: During the use of ICT devices, the number of steps taken by the elderly showed a significant increase (p < 0.05). According to the time series prediction formula, the number of steps predicted on day 94 was 8869.8. In practice, steps on day 94 were 8267.3; the difference between these values was within 10%. Personal health information, health habits, and physiological indicators had a direct impact on pulse manifestation; influence coefficients were 0.14, 0.18, and 0.05 respectively. Conclusion: Through the use of ICT devices, we can understand the health status of the elderly and make behavior predictions. Pulse manifestation data can indicate the health status of the elderly. Thus, ICT devices can be used as health management tools and assist doctors in making simple diagnoses.

    DOI

  • 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  2019.03  [Refereed]

    DOI

  • 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  2018.12

     View Summary

    © 2018 IEEE. This study used wearable devices and traditional Chinese medicine (TCM) diagnosis, which verifies the promotion of wearable devices on the health habits of the elderly, and the correlation between pulse diagnosis and health. We used wearable devices and TCM diagnosis (including TCM doctor diagnosis and Pulse diagnosis instrument) to record health information for the elderly. One-way repeated measures analysis of variance (ANOVA) was used to determine health changes. Correlation analysis was used to determine the relationship between pulse and health indicators. There was significant change in the number of steps for the elderly before and after using the wearable device. Systolic blood pressure (SBP) was negatively correlated with pulse wave time. Diastolic blood pressure (DBP) was negatively correlated with pulse duration. Pulse diagnosis can be used as an indicator to report the health of the elderly. And used wearable devices can quantify health indicators and improve the health awareness.

    DOI

  • 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

    Future Generation Computer Systems   87   591 - 600  2018.10  [Refereed]

     View Summary

    The promise of cross-disciplinary scientific collaboration has recently been proven by both technological innovation and scientific research. Much effort has been spent on research collaboration recommendation. A remaining challenge is to make valuable recommendation to specific researchers in specific fields in order to obtain more fruitful cross-disciplinary collaboration. Cross-disciplinary information hides in big data and the relationships between different fields are complicated, complex, and subtle. This paper proposes a method for cross-disciplinary collaboration recommendation (CDCR) to analyze cross-disciplinary collaboration patterns in scholarly big data, and recommend valuable research fields for possible cross-disciplinary collaboration. A cross-disciplinary discovery algorithm based on topic modeling is designed to extract potential research fields. Collaboration patterns are examined by analyzing the research field correlations. A recommendation algorithm is developed to provide a specific recommendation list of potential research fields according to the discovered cross-disciplinary collaboration patterns with researchers’ profiles. Evaluations conducted based on a real scholarly dataset demonstrate the effectiveness of the proposed method in recommending potentially valuable collaborations.

    DOI

  • 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 )  2018.10  [Refereed]

  • 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)    2018.10  [Refereed]

  • 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  2018.08  [Refereed]

     View Summary

    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

  • 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  2018.08  [Refereed]

     View Summary

    The growth of cyberspace brings more information to service recommendation. The scores of item are used in most of the recommendation algorithms, but the attributes of users and items are rarely involved in trust recommendation in cyberspace. Both the rating features and attribute information are important for trust recommendation results. In this paper, we combine the heterogeneous information in cyberspace and propose a novel trust recommendation model based on the latent factor model and trusty neighborhood fitting model. We utilize the feature based Latent Factor Model and study the linear features integrated model To solve the failure problem of the latent factor model in the integrated model under the cold-start situations, we propose two optimized methods, which contain the filling method based on feature similarity and the filling method based on feature regression through mapping attributes to features. Experimental results show that the improved method outperforms traditional collaborative recommendation in terms of recommendation accuracy. Meanwhile, our proposed method has been verified to free from the impact of the cold-start problem.

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  • 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)    2018.08  [Refereed]

  • 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  2018.06  [Refereed]

    DOI

  • 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     1 - 16  2018.05  [Refereed]

     View Summary

    Twitter is one of the most popular social network services (SNS) applications, in which users can casually post their messages. Given that users can easily post what they feel, Twitter is widely used as a platform to express emotions. These emotional expressions are considered to possibly influence user relationships on Twitter. In our previous study, we analyzed this influence using emotional word dictionaries. However, we could not measure the emotion scores for the words not included in the dictionaries. To solve this problem, in this study, we use the Naive Bayes and consider dependency parsing, i.e., the structure of tweets and the relationships of words. Furthermore, we introduce a set of new measures, namely total positive emotion score (TPES), total negative emotion score (TNES), and total neutral emotion score (TNtES). Based on these measures, we define a new composite index (CI) for emotion scores, which is a normalized value in the range of 0 to 1. We categorize users into positive and negative groups based on the composite index and test the difference of user relationships between these two groups with a statistical method. The result demonstrates that the relationships of positive users not only get better (i.e., the number increases) with time, but also tends to be mutual, which is consistent with the result of our previous study.

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  • 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 )  2018.05  [Refereed]

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  • 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  2018.04  [Refereed]

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  • 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  2018.03  [Refereed]

    DOI

  • Optimization modeling and analysis of trustworthiness determination strategies for service discovery of MSNP

    Xixi Ma, Qun Jin, Julong Pan, Yufeng Wang

    Journal of Supercomputing     1 - 17  2018.02  [Refereed]

     View Summary

    In trustworthy service discovery for Mobile Social Networking in Proximity (MSNP), conventional trust computation faces a big challenging issue—relatively high latency. To cope with it, trustworthiness determination strategies were proposed in our previous study, aiming at avoiding trust computation under certain conditions, so as to reduce the latency. These strategies are conceived based on the assumption that data of a user’s past experience and current profile could be used, and they are incorporated with a set of thresholds from the analysis result of these data. The settings of these thresholds directly affect service quality and user satisfaction on the MSNP service, which in turn becomes an optimization problem. In this paper, we focus on formulating this optimization problem and demonstrating the effectiveness of our proposed solution by designing a simulation experiment. In detail, we establish mathematical models and adjust parameters. We conduct simulations on MATLAB and analyze the results obtained under several different settings. We further compare our work with related works. The results show that our proposed solution is practically feasible and effective in reducing latency under certain conditions.

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  • 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  2018.02  [Refereed]

     View Summary

    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.

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  • Overlap community detection using spectral algorithm based on node convergence degree

    Weimin Li, Shu Jiang, Qun Jin

    Future Generation Computer Systems   79   408 - 416  2018.02  [Refereed]

     View Summary

    Community structure is a typical feature of complex networks in cyberspace, and community detection is considered to be crucial to understanding the topology structure, network function and social dynamics of cyberspace. However, some particular nodes may simultaneously belong to several communities in cyberspace. Though there are many algorithms to detect the overlapping communities, most of them are based on the network structure without considering the attributes of the nodes. In this paper, we focus on the convergence characteristic of network and propose an overlap community detection algorithm based on the node convergence degree, which is defined as a combination of attribute convergence degree and structure convergence degree. It combines the network topology with the attributes of the nodes and considers both local and global information of a node. An improved PageRank algorithm is used to get the importance of each node in the global network, while the information of local network is used to measure the structure convergence degree. The overlap communities are thus identified by spectral cluster based on the node convergence degree. Finally, experiment results demonstrate the effectiveness and better performance of our proposed method.

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  • Influence analysis of emotional behaviors and user relationships based on Twitter data

    Kiichi Tago, Qun Jin

    Tsinghua Science and Technology   23 ( 1 ) 104 - 113  2018.02  [Refereed]

     View Summary

    One of the main purposes for which people use Twitter is to share emotions with others. Users can easily post a message as a short text when they experience emotions such as pleasure or sadness. Such tweet serves to acquire empathy from followers, and can possibly influence others' emotions. In this study, we analyze the influence of emotional behaviors to user relationships based on Twitter data using two dictionaries of emotional words. Emotion scores are calculated via keyword matching. Moreover, we design three experiments with different settings: calculate the average emotion score of a user with random sampling, calculate the average emotion score using all emotional tweets, and calculate the average emotion score using emotional tweets, excluding users of few emotional tweets. We evaluate the influence of emotional behaviors to user relationships through the Brunner-Munzel test. The result shows that a positive user is more active than a negative user in constructing user relationships in a specific condition.

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  • 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  2018.01  [Refereed]

     View Summary

    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

  • 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  2018  [Refereed]

  • 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  [Refereed]

  • 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  [Refereed]

  • 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  [Refereed]

  • 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    2018  [Refereed]

  • 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  [Refereed]

    DOI

  • 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  2017.12  [Refereed]

     View Summary

    In this study, we use wearable devices to monitor the health and physiological indicators of the elderly, and analyze the effects of the elderly's walking steps and sleep as the measurable health and physiological indexes. Eighteen cases of the elderly who received health management services are selected. We establish the generalized linear mixed model, and Pearson correlation analysis result shows statistically significant for the number of walking steps and systolic blood pressure/diastolic blood pressure. The number of walking steps is positively correlated with the systolic/diastolic pressure. The more walking steps and the better the sleep quality, the more stable the daily blood pressure is. Therefore, it is possible to effectively control the elderly's blood pressure by exercising and managing sleeping. It can be better for the elderly to have self-esteem health managed by using wearable devices, and encourage the elderly to exercise at a certain extent.

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  • 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  2017.12  [Refereed]

     View Summary

    In recent years, recommender systems are widely applied in e-commerce system to help users locating their interested information. However, the 'all good reputation' problem brings down the accuracy of recommender systems. In addition, users' social network can benefit the recommendation especially when dealing with cold-start scenarios. In this paper, a novel trust-aware recommendation approach for e-commerce is proposed, which unearths the hint from ordinary rating and trust network by users' instant interactions in e-commerce system. More precisely, a rating revamping algorithm is designed to extract semantic ratings from feedback comments, and further construct fine grained rating score for the next process. Then, the recommendation scheme is studied through analyzing the users' trust network and their own behavior in e-commerce system. Finally, evaluations conducted based on a real dataset 'Douban' to demonstrate the effectiveness of the proposed method.

    DOI

  • 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  2017.12  [Refereed]

     View Summary

    As an SNS, Twitter is popular because users can post their emotions as a short message easily. Emotional tweets may influence user relationships. In our previous study, we found that positive users construct mutual relationships in Twitter. Keyword matching with emotional word dictionaries was used to detect positive users. The problem of keyword matching is the limitation of word number. To solve this problem, we use machine learning, specifically Naive Bayes Classification, to classify emotions of tweets. We analyze whether there is a difference in user relationships between the positive and negative groups by the Brunner-Munzel test. The result shows that the relationships of positive users increase more than that of negative users in the followee fluctuation, follower fluctuation and mutual follow fluctuation, which means that a positive user is more active to construct user relationships than a negative user.

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  • 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  2017.11  [Refereed]

     View Summary

    Data intensive computing (DIC) provides a high performance computing approach to process large volume of data. In this study, a new formalization is introduced to present the two-stage DIC task execution in a stream manner. A novel heuristic algorithm is proposed for the scheduling problem due to the NP complexity. The theoretical approximation ratio bounds for the heuristic are analyzed and confirmed by the experimental evaluation. Overall, we observe that the proposed method conducts average 1.2 times makespan than the theoretic bound of the optimal solution. Besides, the proposed method outperforms the GA and FIFO scheduling schemes with overall improvements. (C) 2017 Elsevier Inc. All rights reserved.

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  • 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  2017.11  [Refereed]

  • 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)    2017.10  [Refereed]  [International coauthorship]

    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  2017.09  [Refereed]

     View Summary

    In recent years, cross-disciplinary scientific collaboration has been proved to be promising for both research practice and innovation. Lots of efforts have been spent in collaboration recommendation. However, the cross-disciplinary information is hidden in tons of publications, and the relationships between different fields are complicated, which make it challengeable recommending cross-disciplinary collaboration for a specific researcher. In this paper, a novel cross-disciplinary collaboration recommendation method (CDCR) that unearths the common cross-disciplinary collaboration patterns and historical scientific field preferences of authors is proposed to recommend potential cross-disciplinary research collaboration. In CDCR, a research field discovery algorithm is designed to classify scientific topics obtained from the publications into the correct field automatically. Then, the collaborative patterns are studied through analyzing the composition fields and the corresponding percentage of all publications. Furthermore, we investigate the common correlation of different research fields. Based on the common correlation and the researcher's specific pattern, the most valuable fields will be listed by CDCR. The effectiveness of our approach is evaluated based on a real academic dataset.

    DOI

  • 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  2017.09  [Refereed]

     View Summary

    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

  • 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  2017.09  [Refereed]

     View Summary

    Recently, Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones. Unlike traditional OTT (Over-The-Top) based proximal social services (like Foursquare, etc.), in which the centralized server (usually located in the cloud) receives periodic location updates from users' mobile devices (e.g., using GPS, etc.), and then determines proximity based on gathered locations and interests, D2D based proximity services (MSNPs) support infrastructure-free and self-organized social networking, allowing users to share experiences in real time and in a specific place, which are more fun, and can significantly increase users' engagement. However, the glaring absence of the practical MSNP solutions on the market is alarming, due to the lack of comprehensive understanding of architecture, technologies and development frameworks available (advantages/disadvantage, applicability, etc.), as well as special requirements of MSNPs. This paper thoroughly investigates D2D based MSNP architecture, key challenges and their potential solutions on smartphones, organized as layers from bottom to up, presents how to utilize commercial off-the-shelf existing technologies and development frameworks to quickly and easily build MSNP applications, and summarizes the unsolved issues in popular development frameworks (e.g., AllJoyn, etc.). Our primary goal is, for commercially available smartphones, to identify key challenges in various layers of MSNP architecture, potential development frameworks and solutions, provide quick how-to-do for developers of MSNP applications, and greatly facilitate to develop and deploy interesting and commercially potential MSNP applications. (C) 2015 Elsevier B.V. All rights reserved.

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  • 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  2017.09  [Refereed]

     View Summary

    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.

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  • 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  2017.07  [Refereed]

     View Summary

    With the rapid development of mobile networks, people are no longer limited to seeking information offline. The Internet provides a good choice for them. As the previous research work shows, more and more people get used to using the Internet to search for health information. Online health information has attracted much attention ever before. It is well known that health related information generated on the Internet contains a large amount of practical data, which can be utilized for health related study. In this paper, firstly we review related research work on self-disclosure and online behavior related to health information. We analyze and summarize factors relevant to health concerns, and discuss measuring dimensions for health concerns. Finally, we present a basic health concern model and future direction for health concern analysis based on online health information behaviors and social data.

    DOI

  • 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  2017.05  [Refereed]

     View Summary

    The development of social media provides convenience to people's lives. People's social relationship and influence on each other is an important factor in a variety of social activities. It is obviously important for the recommendation, while social relationship and user influence are rarely taken into account in traditional recommendation algorithms. In this paper, we propose a new approach to personalized recommendation on social media in order to make use of such a kind of information, and introduce and define a set of new measures to evaluate trust and influence based on users' social relationship and rating information. We develop a social recommendation algorithm based on modeling of users' social trust and influence combined with collaborative filtering. The optimal linear relation between them will be reached by the proposed method, because the importance of users' social trust and influence varies with the data. Our experimental results show that the proposed algorithm outperforms traditional recommendation in terms of recommendation accuracy and stability.

    DOI

  • A heuristic approach to discovering user correlations from organized social stream data

    Xiaokang Zhou, Qun Jin

    MULTIMEDIA TOOLS AND APPLICATIONS   76 ( 9 ) 11487 - 11507  2017.05  [Refereed]

     View Summary

    Recently, with the widespread popularity of SNS (Social Network Service), such as Twitter, Facebook, people are increasingly accustomed to sharing feeling, experience and knowledge with each other on Internet. The high accessibility of these web sites has allowed the information to be spread across the social media more quickly and widely, which leads to more and more populations being engaged into this so-called social stream environment. All these make the organization of user relationships become increasingly important and necessary. In this study, we try to discover the potential and dynamical user correlations using those organized social streams in accordance with users' current interests and needs, in order to assist the collaborative information seeking process. We develop a heuristic approach to build a Dynamically Socialized User Networking (DSUN) model, and define a set of measures (such as interest degree, and popularity degree) and concepts (such as complementary tie, weak tie, and strong tie), to discover and represent users' current profiling and dynamical correlations. The corresponding algorithms are developed respectively. Finally, the architecture of the functional modules is presented, and the experiment results are demonstrated and discussed based on an application of the proposed model.

    DOI

  • 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  2017.05  [Refereed]

     View Summary

    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

  • 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  2017.05  [Refereed]

     View Summary

    Falling accidents cause severe damage to human health, especially to the elderly. Nowadays, smartphones are ubiquitous and widely used around the world, in which rich sensors are embedded. Thus, a smartphone based falling detection system, SmartFDS is proposed in this paper, which can recognize the associated individual's falling behavior and send out an emergent message containing the location for immediate help. Generally, SmartFDS includes offline training phase and online activity recognition phase. Specifically, in training phase, utilizing the embedded accelerometer sensor, falling data for various situations are collected to extract the desired features that can appropriately characterize the falling behavior. Considering that the raw data are intrinsically prone to noise and error, those data are preprocessed by weighted smoothing. Then, 6 time-domain features are elaborated to determine the discriminative features for characterizing falling, and two features, maximum and vertical velocity are selected. Then, 4 different classification algorithms are investigated, and SVM is selected. The prototype of SmartFDS is implemented on Android phones, and can detect falling in real time accurately.

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  • Mobile crowdsourcing: framework, challenges, and solutions

    Yufeng Wang, Xueyu Jia, Qun Jin, Jianhua Ma

    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE   29 ( 3 )  2017.02  [Refereed]

     View Summary

    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.

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  • 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  2016.11  [Refereed]

     View Summary

    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

  • 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  2016.08  [Refereed]

     View Summary

    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

  • 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  2016.07  [Refereed]

     View Summary

    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

  • 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  2016.06  [Refereed]

     View Summary

    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

  • An Integrated Incentive Framework for Mobile Crowdsourced Sensing

    Wei Dai, Yufeng Wang, Qun Jin, Jianhua Ma

    TSINGHUA SCIENCE AND TECHNOLOGY   21 ( 2 ) 146 - 156  2016.04  [Refereed]

     View Summary

    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

  • 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  2016.02  [Refereed]

    DOI

  • Gradually adaptive recommendation based on semantic mapping of users′ interest correlations

    Jian Chen, Xiaokang Zhou, Qun Jin

    International Journal of Communication Systems   29 ( 2 ) 341 - 361  2016.01  [Refereed]

     View Summary

    SUMMARY In this paper, we propose a gradually adaptive recommendation model based on the combination of both users' commonalities and individualities that depend on the semantic mapping of users' interest correlations. We analyze users' information access behaviors and histories to extract users' interests and trace their transitions. In details, according to a set of bookmark tags classified by a semantic means, the pages accessed by users are assigned into several tag classes, which will finally be clustered into different groups in accordance with the types of interests that belong to two categories: personal and common interests, respectively. Based on the detection of users' interest focus transitions through interactions between users, we provide a series of information seeking actions in sequence to the target users. Besides, according to the reference groups which are defined to describe different relations with the target users, the successful experience is extracted and recommended. After the description of the definitions and measures, the mechanism to infer the interest focus, the system architecture and experimental evaluation results are described and demonstrated.

    DOI

  • Gradually adaptive recommendation based on semantic mapping of users interest correlations

    Jian Chen, Xiaokang Zhou, Qun Jin

    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS   29 ( 2 ) 341 - 361  2016.01  [Refereed]

     View Summary

    In this paper, we propose a gradually adaptive recommendation model based on the combination of both users' commonalities and individualities that depend on the semantic mapping of users' interest correlations. We analyze users' information access behaviors and histories to extract users' interests and trace their transitions. In details, according to a set of bookmark tags classified by a semantic means, the pages accessed by users are assigned into several tag classes, which will finally be clustered into different groups in accordance with the types of interests that belong to two categories: personal and common interests, respectively. Based on the detection of users' interest focus transitions through interactions between users, we provide a series of information seeking actions in sequence to the target users. Besides, according to the reference groups which are defined to describe different relations with the target users, the successful experience is extracted and recommended. After the description of the definitions and measures, the mechanism to infer the interest focus, the system architecture and experimental evaluation results are described and demonstrated. Copyright (c) 2014 John Wiley & Sons, Ltd.

    DOI

  • 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  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    Nowadays, we are living in a well-suited social environment with a variety of lifestyles and values. Life support has become important in such a diversified society. Along with continuously collecting the tremendous amount of personal big data generated in the social environment, it is possible for us to provide the life support based on personal data analytics. Moreover, analyzing such a kind of data can facilitate deep understanding of individual life. In this study, we focus on personal data analytics to support well-being oriented life. Three categories of personal data are classified from the collection of individuals' daily life data, and a framework of well-being oriented personal data analysis is proposed, which can provide people with suggestions and advices to improve their living life.

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  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    Community structure is a common feature in real-world network. Overlap community detection is an important method to analyze topology structure and function of the network. Most algorithms are based on the network structure, without considering the node attributes. In this paper, we propose an overlapping community detection algorithm based on node convergence degree which combines the network topology with the node attributes. In our method, PageRank algorithm is used to get the importance of each node in the global network and utilize the local network (local neighbors) to measure the structure convergence degree. Then, node convergence degree combining node attributes and structure convergence degree is designed. Finally, the overlap communities can be identified by the Spectral Cluster based on node convergence degree. Experiments results demonstrate effectiveness and better performance of our method.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we concentrate on a feasibility study on personal data analysis for well-being oriented life support. We introduce our basic concept and model to describe the personal data collected from people's daily life, and discuss how to utilize the personal analysis to provide users with the individualized services in their daily lives. Finally, we present the experimental analysis based on people's daily activity data, to demonstrate the feasibility of our proposed approach.

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  • 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  [Refereed]

     View Summary

    The world has become an aging society with exponentially increasing social security benefit expenditure and nursing care costs. To help solve these issues and challenges, utilization of advanced ICT is highly expected to allow more elderly people to remain independent for their proactive social participation irrespective of age. In this study, we propose a human-centric safe and secure framework of ubiquitous living environments (Ubi-Liven) for the elderly people towards seamless integration of the cyber-enabled ubiquitous holistic living support system with a physical living environment. We further address and discuss the design and technical issues for the implementation of a smart living environment on the fly under the proposed framework, empowered by ubiquitous assistive technologies such as cloud, IoT and big data analytics based on life logs to provide holistic support for the elderly's activities of daily living and healthcare.

    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  [Refereed]

     View Summary

    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  [Refereed]

     View Summary

    Nowadays, the analysis of social networks, as well as the community evolution has become a hotly discussed topic in social computing field. In this paper, we focus on mining and tracking the dynamic communities based on social networking analysis. Based on a generic framework for the dynamic community discovery, a computational approach is developed to extract users' static and dynamic features for the temporal trend detection. A dynamically socialized user networking model is then presented to describe users' various social relationships. A mechanism is proposed and developed to detect the dynamic user communities, and track their evolving changes. Experiments using Twitter data demonstrate the effectiveness of our method in tracking how communities dynamically create, split, and merge from a group of connected people in social media environments.

    DOI

  • 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  2015.12  [Refereed]

     View Summary

    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.

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  • 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  2015.10  [Refereed]

     View Summary

    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.

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  • 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  2015.08  [Refereed]

     View Summary

    With the development of social network services, the user relation spectrum of the social network has exceeded our imagination. Hence, personalized recommendation algorithms are adopted in many social networking sites to help users find their potential friends and related information more quickly and conveniently. In this paper, we discuss the weaknesses of current algorithms, and propose a user profile integrated dynamic social recommendation algorithm in order to overcome those limitations. Finally, through the experiment on Weibo dataset, it can conclude that the proposed algorithm outperforms traditional approaches in terms of accuracy and stability.

    DOI

  • 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  2015.07  [Refereed]

     View Summary

    In this study, we concentrate on analyzing and building the dynamical user profiling to describe users' multi-dimensional features and properties, in order to assist the individualized information seeking and recommendation process in social networking environments. A set of user attributes are introduced and defined to describe the basic user profiling in accordance with the analysis of information behaviors, and several centrality based measures are proposed and developed to describe the users' importance and contributions with regards to a group of users based on their social connections in the DSUN (Dynamically Socialized User Networking) model. The experimental results are discussed to demonstrate the feasibility and effectiveness of our proposed methods.

    DOI

  • 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  2015.07  [Refereed]

     View Summary

    With the increasing popularity of social network services, a tremendous amount of information has been produced. And with more and more users involving in the SNS environment, their network relationships have become as complex as in the real world. In order to find out the useful information more efficiently, in this study, we propose a participatory search and recommendation system based on users' social roles and their relationships in the SNS environment. The proposed system is used to filter users and their messages in a participatory way by analyzing their social roles and connection networks between each user, which can further contribute to personalized information search and recommendation. We describe the design and implementation issues of a prototype system, and discuss how to use the social roles and connection networks to support and empower information search and recommendation.

    DOI

  • 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  2015.07  [Refereed]

     View Summary

    Collaborative filtering (CF) is a popular method for the personalized recommendation. Almost all of the existing CF methods rely only on the rating data while ignoring some important implicit information in non-rating properties for users and items, which has a significant impact on the preference. In this study, considering that the average rating of users and items has a certain stability, we firstly propose a personalized fitting pattern to predict missing ratings based on the similarity score set, which combines both the user-based and item-based CF. In order to further reduce the prediction error, we use the non-rating attributes, such as a user's age, gender and occupation, and an item's release date and price. Moreover, we present the deviation adjustment method based on the support vector regression. Experimental results on MovieLens dataset show that our proposed algorithms can increase the accuracy of recommendation versus the traditional CF.

    DOI

  • 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  2015.07  [Refereed]

  • 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  2015.05  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    In recent years, mainly driven by the availability of modern mobile devices with cheap integrated position sensors, location based services (LBS) have become more and more popular. Prominent examples are nearest friends finding in mobile social networks and the points of interest finders such as the nearest gas stations, hospitals, or places of interests etc. However, the users' privacy information such as location is threatened, when users enjoy the convenience and effectiveness provided by such location services. Therefore, how to secure users' privacy information must be taken into consideration. Many different approaches have been proposed to protect users' identity, location and so on. This paper reviews and analyzes existing privacy protection research works from an integrated perspective, gives the LBS category from two views, and discusses the challenges of securing privacy information. Lastly, our suggestions for future research works are presented.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    Micro-Learning is a new leaning paradigm based on microblogging, e-mail or SMS, in which an integral learning resource consists of a series of micro learning units that are dispersed via the services of Internet, and can be used to help users learn at anywhere with a short-term. But the problem is that most of the micro learning units are disorganized. Therefore, it is a critical issue how to organize these micro learning units, in order to make them easier to be used and learned. In this study, we propose an approach based on process mining to organize the learning units according to the situation of users. Firstly, the successful micro-learning processes are extracted from the access logs. And then, the learning process map named navigation map is created based on the domain knowledge and the access sequence of users. Secondly, according to the similarity of access behavior, a reference user group is extracted dynamically for a target user. Based on the dynamic Bayesian network, the navigation map is then used to calculate the posterior probabilities of learning units. Finally, on the basis of posterior probabilities, a learning unit can be recommended for the target user to learn as the next step. The results are provided to the target user gradually, until the target user finish the whole course by the guide of learning process at his/her fragmented time.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    With the help of several emerging computing paradigms, such as Ubiquitous Computing, Social Computing, and Mobile Computing, OLP (Open Learning Process) has become an important research issue in the online learning environment. It becomes possible to share the learning process related information in and cross systems to meet the needs of all stakeholders, such as teachers, learners and managers. In this study, we focus on the OLP in the social learning environment based on the personal and social analytics, which can provide users with the process-oriented learning support. We present a data processing framework to collect, analyze, and organize the learning-related data in a user-centric way. Three important issues regarding to the unified data management, socialized learning analytics, and sharable open learning process are discussed towards the process-oriented learning innovation. Based on these, an open learning platform is proposed and designed to provide users with the individualized support in the collaborative learning process.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    In this paper, an approach to presenting the learning resources, especially those existing user-generated contents associated with learners' activities, as the recommendation to satisfy their current requirements in a social media enhanced learning system, is proposed. Users' attentions are caught and analyzed from the browsing behaviors of learners on a webpage through an eye-tracking device.

    DOI

  • 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  [Refereed]

     View Summary

    Data intensive computing (DIC) offers an attractive option for business to remotely execute applications and load the computing resources from cloud in a streaming way. A key challenge in such environment is to increase the utilization of cloud cluster for the high throughput processing. One way of achieving this goal is to optimize the execution of computing jobs on the cluster. We observe that the order in which these jobs are executed can have a significant impact on their overall completion time (makespan). Our goal is to design a job scheduler that minimizes the makespan. In this study, a new formalization is introduced to present each job as a pair of disk processing and network transmitting two-stage durations. Due to the streaming processing feature, the two-stage operations are executed in an overlap manner and may lead to both one-stage and two-stage scheduling situations. A novel heuristic scheduling strategy is proposed for this hybrid scheduling problem, and the performance of the method is confirmed by the experimental evaluation.

    DOI

  • 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  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    Comparing to the ordinary text analysis and recommendation, the contents on Social Network Services (SNS) are observably more distinct and less redundant. Content-based recommendation has become the main method on SNSs. Because the limited contents are occurred in SNSs, a considerable effect can’t be reached by using ordinary cluster algorithms. In this paper, we propose a two-phase hybrid clustering algorithm based on Suffix Tree Clustering (STC), which not only uses the words themselves, but relations between them as well. Evaluation experiment and analysis confirm that our techniques have better recommendation results and effects on cold-start scenarios.

    DOI

  • 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  2014.12  [Refereed]

    DOI

  • 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  2014.12  [Refereed]

     View Summary

    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

  • 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  2014.09  [Refereed]

     View Summary

    As more and more users use the mobile terminals of high computing power, the location-based services (LBS) recommendations for mobile users have become an important and interesting topic. Mobile users are eager to get their interested and reliable services quickly. A considerable number of research works have been dedicated to service recommendation based on users' preferences and locations. In this paper, we study the credibility of recommended services, and propose a set of composite measures on how to provide more reliable services. We further propose the trustworthy Skyline of LBS recommendation in terms of the trust degree based on the newly introduced composite measures to achieve more credibility to provide recommendation services. Experimental results show that our method can recommend desired and trusted services to users.

    DOI

  • 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  2014.08  [Refereed]

     View Summary

    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

  • 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  2014.07  [Refereed]

    DOI

  • 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  2014.07  [Refereed]

     View Summary

    In the Internet of Things (IoT) environment, real-time servers run with many uncertain factors. The modeling and validation for the dynamic service composition of location based services (LBS) in the IoT environment are essential, but it is difficult to consider these uncertain factors. In this paper, after analyzing the advantage and shortage of traditional modeling methods, with the introduction of probability, we propose a Color Probability-TCPN (CP-TCPN) by using the tokens with specific colors. The analysis and functional validation methods based on CP-TCPN are proposed and described. After using it to model and analyze the LBS based in the IoT environment, we demonstrate the result which indicates the CP-TCPN based approach can satisfy the modeling and analysis of the IoT based real-time system with uncertain factors.

    DOI

  • 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    2014.07

  • Special section on human-centric computing Preface

    Qun Jin, Sethuraman Panchanathan, Changhoon Lee

    INFORMATION SCIENCES   257   229 - 230  2014.02  [Refereed]

    DOI

  • 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  2014.02  [Refereed]

     View Summary

    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

  • 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)    2014.02  [Refereed]

  • 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  [Refereed]

     View Summary

    Almost all of the existing Collaborative Filtering (CF) methods rely only on the rating data while ignoring some important implicit information in non-rating properties for users and items, which have a significant impact on the preference. In this study, considering that the average rating of users and items have a certain stability, we firstly propose a personalized fitting pattern to predict missing ratings based on the trusty score set, which combines both the user-based CF and item-based CF. In order to further reduce the prediction error, we use the non-rating attributes, such as a user's age, gender and occupation, and an item's release date and price. Moreover, we present the deviation adjustment method based on the Support Vector Regression (SVR). Experiment results show that our proposed algorithms can increase the accuracy of recommendation versus the traditional CF.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    Location Based Services (LBS) is a kind of real-time service with uncertain factors, and its modeling and validation is essential. In this paper, with the introduction of probability, we propose a Color Probability-TCPN (CP-TCPN) by using the tokens with specific colors as the research objects and redefining several relative parameters. We use CP-TCPN to realize modeling and functional verification of the dynamic services composition for LBS. Simulation result is presented to illustrate the application of CP-TCPN in the modeling and analyzing of the real-time system with uncertain factors. © Springer-Verlag Berlin Heidelberg 2014.

    DOI

  • 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  [Refereed]

     View Summary

    In real human society, influence on each other is an important factor in a variety of social activities. It is obviously important for recommendation. However, the influence factor is rarely taken into account in traditional recommendation algorithms. In this study, we propose an integrated approach for recommendation by analyzing and mining social data and introducing a set of new measures for user influence and social trust. Our experimental results show that our proposed approach outperforms traditional recommendation in terms of accuracy and stability. © 2014 Springer-Verlag Berlin Heidelberg.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    In this study, learning support in a blended learning environment integrated with social media is concentrated on. A method is proposed to integrate the S-UPS (Socialized Ubiquitous Personal Study), which is utilized to collect and manage social stream data, into a blended learning system so as to combine the best aspects of both face-to-face and online instructions for the improvement of learning efficiency and enrichment of learning experience. Based on these, an empirical study is conducted to show the feasibility and effectiveness of our proposed method. Experimental evaluation analysis of the system reveals the enhancement of learning process in the blended learning environment. © 2014 Springer-Verlag.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we focus on the deep analysis of the learning behavior patterns in the task-oriented learning process, which aims to extract and describe the sharable learning processes for adaptive learning support. The LA-Patterns are extracted to represent an individual's learning behavior patterns. Three categories, named Regular Patterns, Successive Patterns, and Frequent Patterns, are classified to describe users' learning patterns with different features, which can be utilized to recommend users with the adaptive learning process as the learning guidance. The experiment and analysis results in a learning management system are discussed finally. © 2014 Springer International Publishing.

    DOI

  • 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  2013.12  [Refereed]

     View Summary

    Differing from many studies of recommendation that provided the final results directly, our study focuses on providing an optimized process of information seeking to users. Based on process mining, we propose an integrated adaptive framework to support and facilitate individualized recommendation based on the gradual adaptation model that gradually adapts to a target user's transition of needs and behaviors of information access, including various search-related activities, over different time spans. In detail, successful information seeking processes are extracted from the information seeking histories of users. Furthermore, these successful information seeking processes are optimized as a series of action units to support the target users whose information access behavior patterns are similar to the reference users. Based on these, the optimized information seeking processes are navigated to the target users according to their transitions of interest focus. In addition to describing some definitions and measures introduced, we go further to present an optimized process recommendation model and show the system architecture. Finally, we discuss the simulation and scenario for the proposed system.

    DOI

  • 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  2013.12  [Refereed]

     View Summary

    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

  • 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  2013.10  [Refereed]

     View Summary

    "U-Business" is a novel type business environment, which can provide various services via many mobile devices. In order to provide personalized service to different users, user model (UM) can play an important role in U-Business. UM reflects some characteristics of users to a certain degree, which is used widely in U-Business, like personalized recommendation, social computing, information retrieval services, and so on. Currently, there are more and more researchers who focus on the building and update of UM based on the activities of people. However, as too many UM appeared, the number of UM in cyber space is increasingly large, which takes a lot of space and cost. Furthermore, after some users disappear in the physic world, their models are still working in the cyber world. This case is not reasonable obviously, but few researches take care about it. Therefore, one of important issues, the death of UM should be taken into account in the whole life-cycle of user model. This paper proposes a specific user modeling method for the Cyber Individuals (Cyber-I) in U-Business. The essential difference between this UM and traditional ones is that it has a life, that is, birth, growth, and demise, like a life-cycle of Cyber-I. Specially, the significance of UM life ending and five states of UM death are described from an organic viewpoint. In addition, there is a framework of the whole life process of UM. Finally, the proposed idea is applied to the field of personalized service.

    DOI

  • 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  2013.06  [Refereed]

     View Summary

    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

  • 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  2013.03  [Refereed]

     View Summary

    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

  • 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  2013.01  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    In this study, in order to support and facilitate the web-based learning, we concentrate on user learning behavior pattern discovery in a task-oriented learning process. Based on a hierarchical graph model which can describe relations among learning actions, learning activities, learning sub-tasks and learning tasks, we introduce the formal definitions for Learning Action Pattern and Goal-driven Learning Group to discover and represent users' learning behavior patterns within a learning task process. Two integrated algorithms are developed to calculate and generate the Learning Action Patterns for an individual user and the Goal-driven Learning Groups for a number of users, which can benefit sharing of learning activities and improve learning efficiency in e-learning environments. Finally, the design of a prototype system with experiment results is discussed. © 2013 Springer-Verlag.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    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.

  • 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  [Refereed]

     View Summary

    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.

  • 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  [Refereed]

     View Summary

    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

  • Special issue on technology-enhanced social learning

    Chengjiu Yin, Xinyou Zhao, Qun Jin

    International Journal of Distance Education Technologies   11 ( 1 )  2013.01

  • 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  [Refereed]

     View Summary

    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

  • 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  2013.01  [Refereed]

    DOI

  • 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  2012.12  [Refereed]

     View Summary

    Background: In the cloud computing environments, numerous ambient services may be created speedily and provided to a variety of users. In such a situation, people may be annoyed by how to make a proper and optimal selection quickly and economically. Methods: In this study, we propose an Adaptively Emerging Mechanism (AEM) to reduce this selection burden with an interdisciplinary approach. AEM is applied and integrated into the Flowable Service Model (FSM), which has been proposed and developed in our previous study. We consider the user’s feedback information is a pivotal factor for AEM, which contains the user’s satisfaction degree after using the services. At the same time, we assume that these factors, such as the service cost, matching result precision, responding time, personal and social context information, etc., are essential parts of the optimizing process for the selection of ambient services. Results and Conclusion: By analyzing the result of AEM simulation, we reveal that AEM can (1) substantially improve the selection process for LOW feedback users
    (2) bring no negative effect on the selection process for MEDIUM or HIGH feedback users
    and (3) enhance the rationality for services selection.

    DOI

  • Special Issue on Multidisciplinary Emerging Networks and Systems Foreword

    Qun Jin, Yufeng Wang

    JOURNAL OF COMPUTER AND SYSTEM SCIENCES   78 ( 6 ) 1671 - 1672  2012.11  [Refereed]

    DOI

  • 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  2012.11  [Refereed]

     View Summary

    Recently, SNS (Social Network Service), blog and microblog have become very popular. Stream data, a large collection of diverse contents that are created dynamically in the form of streams, have become an important part of the Internet resources. At the same time, it has become easier to collect people's activities as their lifelogs, not only in the cyber space, but also in the physical world by means of ubiquitous and sensing technology. Either stream data or lifelogs represent different aspects of people's information behaviors and social activities, which we call Social Streams. In this study, we try to integrate and organize these social stream data, such as Twitter Tweets, into Ubiquitous Personal Study (UPS) proposed in our previous study. In this paper, we introduce and define a set of new metaphors: Drop, Stream, River and Ocean, to represent a variety of social stream data in different stages, in order to enable UPS socialized toward an individualized information portal. We further propose a Framework of Organic Streams to meaningfully organize these stream data. We discuss the design and implementation issues of a prototype system, and describe the algorithms to realize our proposed metaphors. Moreover, we show a scenario of using the socialized UPS to support learning activities, with experimental data and analysis results. (C) 2011 Elsevier Inc. All rights reserved.

    DOI

  • 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)    2012.08  [Refereed]

  • 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  [Refereed]

     View Summary

    In the study, we propose an integrated adaptive framework to support and facilitate individualized learning through sharing the successful process of learning activities based on similar learning patterns in the ubiquitous learning environments empowered by Internet of Things (IoT). This framework is based on a dynamic Bayesian network that gradually adapts to a target student's needs and information access behaviours. By analysing the log data of learning activities and extracting students' learning patterns, our analysis results show that most of students often use their preferred learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimise the process of learning activities using the extracted learning patterns, infer the learning goal of target students, and provide a goal-driven navigation of individualized learning process according to the similarity of the extracted learning patterns.

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    Recommender system is a focus in the age of information explosion. In this study, with the benefit of social networking service, we propose a User-Centric Integrated Recommendation Model based on combining of users' individualities and commonalities, in which users' interests are focused and their transitions are traced by analyzing users' information access behaviors and histories, and then a sequence of information seeking actions are recommended to target users through dectecting the transitions of their interests focus by interaction of users and the system, and extracting successful experience from a reference user group, in which the reference users are similar to the target users. A set of bookmark tags are used to describe relations of Web pages. The pages accessed by users are classified by the bookmark tags, and grouped into two categories of individual and common interests and their sub-categories. The individual interests are divided into three types: strong interest, weak interest and uncertain interest. The common interests are divided into popular interest, public interest and private interest. In this paper, in addition to describing definitions and measures, we present a mechanism of inferring interest focus and show the system architecture. Finally, the conclusion and further work are introduced. © 2012 IEEE.

    DOI

  • 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  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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    2012  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    Comparing with traditional e-learning, the socialized e-learning system provides us a new paradigm to deliver knowledge through social medias. In this study, we concentrate on the organization of knowledge delivered across the social media enhanced learning environment in order to support the learning process. An integrated approach is proposed to capture users' intentions using eye-tracking technology, and further organize the related social streams into meaningful contents, in which both re-defined and newly created knowledge from interactions among users can be extracted in accordance with users' individualized requirements to assist their learning tasks and finally promote the learning efficiency for both professors and students. © 2012 IEEE.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we try to discover the potential and dynamical user correlations using those reorganized social streams in accordance with users' current interests and needs, in order to assist the information seeking process. We develop a mechanism to build a Dynamical Socialized User Networking (DSUN) model, and define a set of measures (such as interest degree, and popularity degree) and concepts (such as complementary tie, weak tie, and strong tie), which can discover and represent users' current profiling and dynamical correlations. The corresponding algorithms are developed respectively. Based on these, we finally discuss an application scenario of the DSUN model with experiment results. © 2012 Springer-Verlag.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we concentrate on learning activity sharing and individualized recommendation based on dynamical user correlations, in order to support and facilitate the web-based learning process integrated with social streams. A user correlation-based learning activity model is built to demonstrate the relations among user, learning task and learning activity. Based on these, an integrated method is proposed to provide a target user with the possible learning activity as the next learning step, which is expected to enhance the learning efficiency. Finally, design of a Moodle-based prototype system is discussed. © 2012 Springer-Verlag.

    DOI

  • 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  2011.12  [Refereed]

     View Summary

    In this paper we argue a user has to be in the center of information seeking task, as in any other task where the user is involved. In addition, an essential part of user-centrism is considering a user not only in his/her individual scope, but expanding it to the user's community participation quintessence. Through our research we make an endeavor to develop a holistic approach from how to harnesses relevance feedback from users in order to estimate their interests, construct user profiles reflecting those interests to applying them for information acquisition in online collaborative information seeking context. Here we discuss a human-centric integrated approach for Web information search and sharing incorporating the important user-centric elements, namely a user's individual context and 'social' factor realized with collaborative contributions and co-evaluations, into Web information search.

    DOI

  • Pervasive Learning Tools and Technologies

    Neil Y. Yen, Qun Jin, Hiroaki Ogata, Timothy K. Shih, Y. Yano

    Pervasive Computing and Networking     37 - 50  2011.06  [Refereed]

    DOI

  • 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  [Refereed]

     View Summary

    There have been two open questions about Web 2.0 enhanced CoP (Community of Practice). The first one is the isolation of CoPs caused by the variety of web services, and the second one is the context loss in knowledge transference. Both of the questions arise from the discontinuity of the knowledge transference in a CoP or among CoPs. In order to tackle these questions, CAPK (Context, Actor, Pipe and Knowledge object), a new learning process model, is proposed to model learning in the Web 2.0 technology enhanced CoPs. In this model, the premise of learning is the connection to the knowledge objects by various pipes which can be used to maintain a connection with a knowledge object. Context is considered as the most important component of effective learning in this model. CAPK model can provide us a new perspective to tackle the above problems. In order to achieve effective learning in current web based CoPs, flexible connection to and management of knowledge objects are necessary to support learning in CoPs. Besides, a uniform context description is also a requirement. In this paper, after the introduction of the CAPK learning process model, we describe design and implementation of a prototype system for managing the pipes of knowledge objects to provide a solution to transfer context information through Activity Streams specification in and cross various systems. © 2011 IEEE.

    DOI

  • 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  [Refereed]

     View Summary

    Social learning is showing one of the immersive potentialities for human knowledge gathering on the Internet throughout the last decEDe. Due to rapid growth of Internet, people can communicate with each other using IM (Instant Messaging), WWW and P2P. IM Services, such as
    Yahoo, Twitter, Google Talk, ICQ (I seek you), etc. which provides individual and group communications. Web search engines (Google, Yahoo, AOL etc.) collect versatile information by crawling web directories, and web public documents (html, PDF, text, etc.) throughout the world. P2P (Gnutella, Napster, Freenet, etc.) serves file sharing between and/or among users. However, IM, WEB and P2P do not support WW, which indicates WHO the right person/user is and WHAT the right topic a user is looking for. To overcome the WW issues, this research presents a hybrid search engine called P2P-SSE (P2P Social Search Engine) which can find the WW and serves users queries for the support of social learning. © 2011 IEEE.

    DOI

  • 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  [Refereed]

     View Summary

    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

  • 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  [Refereed]

     View Summary

    Sharing learning activity in and cross various systems is a prospective approach to implement OLP (Open Learning Process), a paradigm to share the knowledge generated in the learning process. The question is that the systems supporting teaching and learning are always separated and isolated. To implement OLP, firstly a uniform description of learning activity and a protocol to share learning activity in and cross systems are necessary. Secondly, a systematic framework to support learning activity description is also important. In this research, first, we show our vision of OLP by introducing metaphors such as a drop or an ocean of learning activity. Then based on the analysis of web based learning activity through Activity Theory, we propose a learning activity model to describe learning activity. Moreover, a specification of learning activity streams based on Activity Streams specification is introduced. Finally, a prototype system supporting learning activity streams is implemented based on UPS (Ubiquitous Personal Study) platform. © 2011 Springer-Verlag.

    DOI

  • 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  [Refereed]

     View Summary

    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.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

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    Sharing information and resources on the Internet has become an important activity for education. The use of ubiquitous devices makes 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 places. 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 in order to facilitate search process and to enrich the learning activity. © 2011 ACM.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

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    Recently, social media enhanced learning has become more and more popular. It is featured as learning through interaction and collaboration in a community or across a social network, which can be considered as a kind of social learning. In this study, we integrate SNS (such as twitter) into the web-based learning process and further delve into the discovery of potential information from the reorganized stream data. We propose a Dynamical Socialized User Networking (DSUN) model which represents users' profiling and dynamical relationship by a set of measures. Finally, we show an application scenario of the DSUN model to assist the learning process and enhance the learning efficiency in web-based environments. © 2011 Springer-Verlag.

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  • 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  [Refereed]

     View Summary

    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.

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  • Effective session key distribution for secure fast handover in mobile networks

    Jong Hyuk Park, Qun Jin

    TELECOMMUNICATION SYSTEMS   44 ( 1-2 ) 97 - 107  2010.06  [Refereed]

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    In this paper, we introduce a session key distribution mechanism for fast secure handover in wireless mobile networks. The proposed mechanism is based on the stream control transmission protocol in where a mobile node actively changes its IP address without its connection loss. When a mobile node moves between different access routers, the required session key at a new access router is distributed previously through the tunnel established between the previous access router and the new access router. Due to the reduced key distribution time, the mobile node achieves its secure seamless handover. The provided performance analysis proves that the proposed mechanism provides the reduced signaling cost compared to existing mobility protocols. In addition, the proposed mechanism reduces the handover latency so that the reduced amount of packet loss provides the stable handover performance for real-time applications.

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  • 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  [Refereed]

     View Summary

    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.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

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    In this study, we develop an innovative approach using sharable learning activity to create an open learning network. In this paper, we present our vision of open learning and a framework for sharable learning activities. We further discuss how to utilize open source software to implement a prototype system, and describe the scenarios and features of the proposed framework and system.

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  • 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  [Refereed]

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    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.

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  • 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  [Refereed]

     View Summary

    Recently, SNS, blog and microblog have become very popular. A different form of diversified contents, comparing to traditional static HTML web pages, are so easy to be generated dynamically, and can be provided to users by timeline. These contents are generally processed data streams, and have become an important part of the Internet resources. In this study, we try to integrate these dynamically diversified contents, such as twitter stream data, into Ubiquitous Personal Study (UPS), a personalized virtual study proposed in our previous study. In this paper, we introduce and define a set of new metaphors to represent a variety of data streams, such as Drop, Stream, River, and Ocean. We propose a Framework of Organic Streams to meaningfully organize these stream data. We describe the design and implementation issues of a prototype system, and discuss a scenario of using the enhanced UPS to support learning that utilizes twitter data streams. © 2010 IEEE.

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  • 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  [Refereed]

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  • A new paradigm of ranking &amp; 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  [Refereed]

     View Summary

    With the development of internet and search engine, users are thought to obtain everything through corresponding web services. Although general purpose searching such as one provided by Google is powerful, searching mechanism for different purposes has to rely on specific metadata. We followed SCORM and CORDRA to develop a registry system named MINE Registry for storing and managing the learning objects. 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.

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  • 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  [Refereed]

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    Services are expected to be a promising way for people to use information and computing resources in the emerging ubiquitous network society. In this study, we propose a metaphoric concept called flowable service. It is defined as a logical stream that organizes and provides circumjacent services in such a way that they are perceived by individuals as those naturally embedded in their surrounding environments. We present our view on how some of these problems, such as flexibility, portability and interoperability of services, can be solved using the flowable services to make seamless integration of diverse services in an intuitive "flowable" way possible, thus achieving maximum satisfaction of both service providers and consumers while decreasing the delivery cost of services. Recognizing the importance of the awareness of each individual's context for smooth and accurate provision of services, we conceive the flowable service framework that harnesses users' contexts to enable pro-active support of human activities in a flexible and natural way. Owing to context-awareness, the framework is able to find and integrate the circumjacent services that are considered to be needed by each individual, and create an ambient service environment tailored to his/her particular needs, proclivities and characteristics. © 2010 IEEE.

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  • 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  [Refereed]

     View Summary

    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.

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  • 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  [Refereed]

     View Summary

    Cloud computing, which can provide ubiquitous services, is a nexus of hardware, software, data and people. Service model is an essential part of cloud computing. It is recognized that the service model should provide precise computing results with low costs. However, we think it is not adequate as a computing paradigm if no consideration is made on the human aspects, especially, the factors of end users. In this study, we propose a novel service model: Flowable Service Model (FSM),which aims to provide appropriate services (as a flow) for users in any time and any place, and let them to enjoy ambient life empowered by cloud computing. How to make the services flowing from the cyber world to the real world? Being inspired by James Williams' stream of consciousness theory, we conceive FSM to leverage a variety of personal information, such as users' behaviors and habits. The operational mechanism for FMS is described in this paper. We expect our proposed model can make every user to feel more ambient with available cloud services. © 2010 IEEE.

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  • 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  [Refereed]

     View Summary

    This paper proposes an agent based support system for promoting interactive teaching and learning. The agent based system is developed with the emphasis on learning to know students' characters, habits, and preferences so that the teacher or the system can give students appropriate hints, encouragements, confidents, and as well as influence students gradually without their noticing and feeling of be persuaded and pressured. With more active participation of students in the interactive learning process, the teaching is more effective and the learning is more efficient. ©2010 IEEE.

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  • 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  [Refereed]

     View Summary

    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.

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  • 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  [Refereed]

     View Summary

    The content granularity and context information are two important factors to the efficiency and reusability of learning objects. The context information is necessary to facilitate the discovery and reuse of learning objects stored in global and/or local repositories. However, traditional learning objects are generally not conceived to incorporate with enough context information. Users have to do some extension of the description item set to fit their special use. In this paper, in order to deal with the issue mentioned above, we firstly introduce a context-rich paradigm, the related service driven tagging strategy, and a context model of learning objects. We further explain how to use the context information to realize the adaptive granularity of the content object. Finally, we show a simple concept model for online authoring systems that support the evolution from resource objects to learning objects. ©2010 IEEE.

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  • 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  2010.01  [Refereed]

     View Summary

    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.

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  • Ubiquitous Personal Study: a framework for supporting information access and sharing

    Hong Chen, Qun Jin

    PERSONAL AND UBIQUITOUS COMPUTING   13 ( 7 ) 539 - 548  2009.10  [Refereed]

     View Summary

    The information resources on the Web are diversified, the amount of which is increasing rapidly. Demands for selecting useful information from the Internet, managing personal contents, and sharing contents under control have risen. In this study, we propose the Ubiquitous Personal Study, a framework of personalized virtual study to support accessing, managing, organizing, sharing and recommending information. In this paper, we focus on discussing the framework, and design and implementation issues on how to implement it with Web 2.0 mash-up technology and Open Source Software.

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  • Specification, standards and information management for distributed systems

    Irfan Awan, Qun Jin, Kuo-Ming Chao

    COMPUTER STANDARDS & INTERFACES   31 ( 5 ) 869 - 869  2009.09  [Refereed]

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  • 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  2009.06  [Refereed]

     View Summary

    User profiling is a widely used technique to analyse and store user interests and preferences to apply this knowledge to improve user experiences with information systems. In this research paper, we present an approach for dynamically constructing user profiles, particularly from uniform relevance feedback in information-seeking activities. We propose an inference method for user interests, which we call High-Similarity Sequence Data-Driven (H2S2D) clustering and discuss its peculiarities and show its superiority for the creation of high-quality concepts, which are the elementary constituents of user profiles. To reflect the volatility of user interests and emphasise the steadiness of persistent preferences, we adopt recency, frequency and persistency as the three main criteria for multi-layered dynamic profile construction and update. Copyright © 2009 Inderscience Enterprises Ltd.

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  • 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  [Refereed]

     View Summary

    User-centeredness has become an essential feature of information systems directly interacting with a user. In this paper we emphasize the importance of a user as an active content creator and contributor, community, and their synergy to achieve better user-centeredness in personalized Web search services. For this, we realize individual-community collaborative scheme integrating information search and sharing, and thus benefiting from both individual and community activities. Here we show the details of the scheme, including expertise-based information co-evaluation and collaborative search.

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  • 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  [Refereed]

     View Summary

    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.

  • 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  [Refereed]

     View Summary

    The paper first introduces the concept of flowable service, the basic idea of which is to organize circumjacent services in such a way so that they are perceived by an individual as those naturally embedded in his/her surrounding environment. It is achieved by seamless integration and provision of diverse services in an intuitive "flowable" way. For this, the mechanism responsible for service discovery, composition and provision has to have a good understanding of a user it serves to. We design a framework with a special focus on context-awareness to find and integrate the circumjacent services thought to be needed by each individual at his/her current situation, and thus create an ambient service environment tailored to his/her particular needs and characteristics. Here introduce the framework, its components and process abstraction, and outline some major issues we have to face when implementing our approach.

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  • 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  [Refereed]

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  • 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  [Refereed]

     View Summary

    In this study, we propose a Gradual Adaption Model for a Web recommender system. This model is used to track users' focus of interests and its transition by analyzing their information access behaviors, and recommend appropriate information. A set of concept classes are extracted from Wikipedia. The pages accessed by users are classified by the concept classes, and grouped into three terms of short, medium and long periods, and two categories of remarkable and exceptional for each concept class, which are used to describe users' focus of interests, and to establish reuse probability of each concept class in each term for each user by Full Bayesian Estimation as well. According to the reuse probability and period, the information that a user is likely to be interested in is recommended. In this paper, we propose a new approach by which short and medium periods are determined based on dynamic sampling of user information access behaviors. We further present experimental simulation results, and show the validity and effectiveness of the proposed system. © 2009 IEEE.

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  • 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  [Refereed]

     View Summary

    This research is aimed at a smart music playing environment in which a set of speakers are placed in different locations/rooms and one of the speakers will automatically play a music whenever a user gets close to it. Our study is focused on the design and prototype implementation of such a smart music playing system called U-LAMP (User Location-Aware Music Player). It consists of a server that stores streamed music data, and a set of clients that can receive and play the streamed music from the server. A user carries a RFID tag and can move around. When the user's tag ID is detected by a RFID reader that is connected to a nearby client, the server will switch the transmission of streamed music data from the previous client to the current one. This paper explains in details about how to get a user's location by detecting the user's tag ID, manage RTP-based music data delivery from the server to the client, play a streamed music using JMF, and achieve better audio listening effects during the transition period of handing-over the playing music stream between speakers in different rooms. © 2009 IEEE.

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  • 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  [Refereed]

     View Summary

    With the rapid advancing in electronics, VLSI, and nanotechnology, ubiquitous devices (u-objects) like mobile devices, sensing devices, RFID devices, IC cards, wireless devices, wireless wearable devices, etc. are getting more and more in number, smaller and smaller in size, and even invisible in form. In order to make them work without human involved and interaction, there is necessity of enabling them with intelligent, smart, or autonomic computing capabilities. Of course, intelligent function embedded is a straightforward approach. However, it may be difficult for the tiny devices to embed the intelligent computing capabilities due to their limited capacity and processing power. For a multiple intelligent agents system, it is not efficient to develop and maintain intelligent computing functions for each individual agent. Therefore, the idea is to design an intelligence entity sharing pool in which a requested intelligence entity can be dynamically composed from a number of atomic intelligence entities and complex intelligence entities residing in the intelligence entity pool and posted to virtual objects (v-object) in the v-object server for sharing by ubiquitous devices in the real world. This research is of three main phases: designing the intelligence entity sharing pool
    mapping u-objects to virtual objects (v-objects)
    and developing a framework for intelligence entity sharing. This paper is mainly focused on describing the first two phases. © 2009 IEEE.

    DOI

  • 利用者の情報アクセス行動を推定する逐次適応モデル(セッション2:履歴,状況・行動推定II)

    陳健, シュテイフロマン, 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]   2008 ( 7 ) 19 - 24  2008.12

     View Summary

    本研究では、利用者の情報アクセス行動のデータを、ショート、ミディアム、ロングといった期間やRemarkableやExceptionalなどの特殊カテゴリに分けて収集・解析し、完全ベイジアン推定を基にした逐次適応モデルを提案する。

    CiNii

  • 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  [Refereed]

     View Summary

    With slide-film interface discussed in this paper we propose a new mobile Web search experience. The interface abolishes fatigue-inducing scrolling while preserving "quality" summaries of Web search results to improve the efficacy and efficiency of mobile Web search. The evaluation of the approach shows that the proposed interface is superior to the conventional mobile search method in a number of aspects like easy navigation and good viewability of search results and can be its good alternative.

    DOI

  • 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  [Refereed]

     View Summary

    Relevance feedback is an important source of information about a user and often used for usage and user modeling for further personalization of user-system interactions. In this paper we present a method to infer the user's interests from his/her relevance feedback using an online incremental clustering method For inference of a new interest (concept) and concept update the method uses the similarity characteristics of uniform user relevance feedback It is fast, easy to implement and gives reasonable clustering results. We evaluate the method against two different data sets, demonstrate and discuss the outcomes.

    DOI

  • 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  [Refereed]

     View Summary

    In the situation of information overload we are experiencing today, conventional web search systems taking a one-size-fits-all approach are often not capable of effectively satisfy individual information needs. To improve the quality of web information retrieval, we propose a collaborative personalised search approach that makes an attempt to &apos;understand&apos; and better satisfy the information needs for each and every searching user. We present a web information retrieval framework called Better Search and Sharing (BESS) that Captures user-system interactions, profiles them and induces personal interests that changes over time with an interest-change-driven profiling mechanism that is also extensively used for the co-evaluation of documents found valuable inside a specific search context by users with similar interests.

    DOI

  • 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  [Refereed]

     View Summary

    The information resources on the Web are diversified, and the amount is increasing rapidly. Demands for selecting useful information from the Internet, managing personal contents, and sharing contents under control have risen. In this study, we propose the Ubiquitous Personal Study (UPS), a framework of personalized virtual study 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 2.0 mash-up technology and Open Source Software.

    DOI

  • 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  [Refereed]

     View Summary

    It is well known that alongside with search engine performance improvements and functionality enhancements one of the determinant factors of user acceptance of any search service is the interface. This factor is particularly important for mobile Web search mostly due to small screen limitations of handheld devices. In this paper we propose scrolless mobile Web search interface to decrease search efforts that are multiplied due to these limitations, and discuss its potential advantages and drawbacks over conventional one.

    DOI

  • 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  [Refereed]

     View Summary

    A smart space is a physical spatial environment such as a room that can provide automatic responses according to the contextual information occurring in an environment. The context data is usually acquired via various devices which are installed somewhere in the environment and/or embedded into some special physical objects, called u-objects, which are capable of executing computation and/or communication. However, the devices used in current researches on smart space are either fixed or residing in real. objects, which are incapable of moving by themselves. Likewise, more and more robots have been produced, but most of them are designed and developed based on the assumption that the space surrounding a robot is an ordinary one, i.e., a non-smart space. Therefore, it is necessary to study what additional services can be offered and what specific technical issues will be faced when adding robots to smart spaces. To identify the potential novel services and technology problems, this research is focused on a case study of a u-object finding service performed by a robot in a smart space. This paper presents the design and development of the system prototype robot which can communicate with other devices and can find a u-object with attached RFID tag in a smart room. Some preliminary experiments were conducted and the results verified the functionalities of the system.

    DOI

  • 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  [Refereed]

     View Summary

    Lifelog is a data set composed of one or more media forms that record the same individual's daily activities. One of the main challenging issues is how to extract meaningful information from the huge and complex lifelog data which is continuously captured and accumulated from multiple sensors. This study is focused on the activity models and analysis techniques to process lifelog data in order: to find what events/states are interesting or important, to summarize the useful records in some structured and semantic ways for efficient retrievals and presentations of past life experiences, and to use these experiences to further improve the individual's quality of life. We propose an integrated technique to process the lifelog data using the correlations between different kinds of captured data from multiple sensors, instead of dealing with them separately. To use and test the proposed models and the analysis techniques, several prototype systems have been implemented and applied to some domain-specific lifelog data; such as in improving a group's collaborative efforts in revising a software, in managing kid's outdoor safety care, in providing a runner's workout assistance, and in structuring lifelog image generation, respectively.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we propose a gradual adaption model for estimation of user information access behavior. A variety of users' information access data are collected by unit of a day for each user, and analyzed in terms of short, medium, long periods, and by remarkable and exceptional categories. The proposed model is then established by analyzing the pre-processed data based on Full Bayesian Estimation. We further present experimental simulation results, and show the operability and effectiveness of our proposed model. © 2008 IEEE.

    DOI

  • 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  [Refereed]

     View Summary

    We discuss an approach to enhance conventional IR with contributions (relevance judgments) done by users interacting with a document collection and personalization by profiles inside the collaborative search and sharing system. It is designed to capture user search intentions derived from explicit and implicit feedback and keep analyzed data in layered profiles for further query augmentation, document recommendation and contribution personalization in the form of "subjective index." For profile generation and document evaluation we propose an interest change driven profiling mechanism which reflects all dynamics of user search intentions. © 2007 IEEE.

    DOI

  • 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  2006.05

     View Summary

    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。

    CiNii

  • 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  [Refereed]

     View Summary

    In recent years, a variety of new computing paradigms have been proposed for various purposes. It is true that many of them intend to and really can gratify some of the people sometime, somewhere; a few of them can even gratify some of the people anytime, anywhere. However, at present, none of the computing paradigms intend to gratify all the people anytime, anywhere. With the rapid advance of information technology and the spread of information services, the IT disparity in age, social standing, and race of the people has been expanding and has become a critical social problem of the 21st century. Thus, we have a fundamental question: Can we construct, in a unified methodology, a computing environment that can gratify all the people in all situations, all places and all the time? We propose a novel and inclusive computing paradigm, named ubisafe computing, for studying and providing possible solutions to the above problem. The ultimate goal of ubisafe computing is to build a computing environment in which all people and organizations can benefit from ubiquitous services anytime anywhere with assured and desired satisfaction without worrying or thinking about safety. That is, the ubisafe computing vision emphasizes two basic aspects: ubiquitous safety and ubiquitous satisfaction to all people in all situations. This paper presents the motivations for the ubisafe computing vision but focuses on one basic aspect of ubiquitous safety that covers reliability, security, privacy, persistency, trust, risk, out of control, and other watchfulness while considering novel, essential ubicomp or percomp features of unobtrusive computers, diverse users/people and life-like systems.

  • 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     707 - +  2006  [Refereed]

     View Summary

    We proposed a collaborative information sharing environment based on P2P net-working technology, to support communication among special groups with given tasks, ensure fast information exchange, increase the productivity Of working groups, and reduce maintenance and administration costs in our previous work.
    However, for a social growing community, not only the information exchange/sharing functions are necessary, but also solutions to support users with idea and knowledge publication tools for private purpose or public use are essential. Some private message (personal idea and experience) posting tools (e.g., weblog) and group collaborative knowledge editing tools (e.g., Wikis) are used in practice; the merits of these tools have been recognized.
    In this paper we propose a scalable information sharing solution, which integrates decentralized P2P networking with centralized personal/group media tools. This solution combines the effective tools, such as weblog and Wiki, into P2P-based collaborative groupware system, to facilitate infinite, growing and scalable information management and sharing for individuals and groups.

    DOI

  • 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     669 - +  2006  [Refereed]

     View Summary

    Context is the information, which is created and obtained from the surrounding environment for the interaction between humans and computational services. A generic model is a key accessor to the context in any context-aware applications for ubiquitous computing. In the past decades, a number of context modeling techniques have been proposed e.g. markup scheme based, logic-based, graphical, and ontology-based. Since ontology in its nature is a promising tool to specify concepts and interrelations, it has been widely adopted in context modeling. However, in the rapid changing environments, semantics may vary according to the time factors and dynamic group of users. In this paper, we propose an ontology-based context model with temporal vector space in order to complement this deficiency.

  • 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  [Refereed]

     View Summary

    Nowadays, the World Wide Web offers public search services by a number of Internet search engine companies e.g. Google [16], Yahoo! [17], etc. They own their internal ranking algorithms, which may be designed for either general-purpose information and/or specific domains. In order to fight for bigger market share, they have developed advanced tools to facilitate the algorithms through the use of Relevance Feedback (RF) e.g. Google's Toolbar. Experienced by the black-box tests of the RF toolbar, all in all, they can acquire simple and individual RF contribution. As to this point, in this paper, we have proposed a collaboratively shared Information Retrieval (IR) model to complement the conventional IR approach (i.e. objective) with the collaborative user contribution (i.e. subjective). Not only with RF and group relevance judgments, our proposed architecture and mechanisms provide a unified way to handle general purpose textual information (herein, we consider e-Learning related documents) and provide advanced access control features [15] to the overall system.

  • 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 - 25  2006  [Refereed]

     View Summary

    Distance education, e-learning, and virtual university are similar terms for a trend of modern education. It is an integration of information technologies, computer hardware systems, and communication tools to support educational professionals in remote teaching. This chapter presents an overview of distance education from the perspective of policy, people, and technology. A number of questions frequently asked in distance learning panel discussions are presented, with the suggested answers from the authors. The survey presented in this chapter includes communication, intelligent, and educational technologies of distance education. Readers of this chapter are academic researchers and engineers who are interested in new research issues of distance education, as well as educators and general participants who are seeking for new solutions. © 2007, Idea Group Inc.

    DOI

  • 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  [Refereed]

     View Summary

    Search is not the only activity in information space users are engaged in. Most of time users rediscover things they used to find in the past, and often they just browse without any specific purpose discovering information space around them or with a particular purpose, such as learning miscellaneous information. We propose an approach for designing exploratory information space that makes use of human-centered power of bookmarking for information selection. The information space is built as a result of a search for something a user intends to discover, and serves as a place for rediscoveries of personal findings, socialization and exploration inside discovery chains of other participants of the proposed prototype system. The most important elements of the proposed information space, main elements of the prototype system to be implemented and used to explore the space, and use scenarios are discussed here. © 2006 IEEE.

    DOI

  • 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  [Refereed]

     View Summary

    In this study, we propose and develop an opensource groupware system called NetIsle. NetIsle is a general purpose groupware system for uniform open groups that integrate a number of tools for online collaboration to ensure fast information exchange and sharing, increase the productivity of working groups, and reduce maintenance and administration costs. The main technologies used for the construction of the system are peer-to-peer (P2P) and push, which are best fitted to those principles and beliefs we build our system upon. © Emerald Group Publishing Limited.

    DOI

  • 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     804 - 806  2005  [Refereed]

     View Summary

    This paper outlines anew model of ubiquitous computing technology support learning (uLearning). In the uLearning, in order to facilitate the awareness of other helpful learners, increase the availability of the mutual and friendly support in the learning process, and enhance learners' communication skills, the authors offer a serial of services. These services arc designed as dynamic group construction service, social intercommunion facilitation service, service of navigating learner to get out of difficulty, etc.

  • 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  [Refereed]

     View Summary

    With advanced technologies, computer devices have become smaller and powerful. As a result, many people enjoy ubiquitous learning using mobile devices such as Pocket PCs. Pocket PCs are easy to carry and use as a distance learning platform. In this paper, we focus on the issues of transferring the current PC based Sharable Content Object Reference Model (SCORM) to Pocket PC based. We will also introduce the Pocket SCORM Run-Time Environment (RTE) which has been developed in our lab. Pocket SCORM architecture is able to operate, even when the mobile device is off-line. It will keep the students' learning record. When it is on line, the records will then be sent back to Learning Management System (LMS). With memory limitation, we provides course caching algorithm to exchange the course content on the Pocket SCORM.

  • 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     230 - 236  2005  [Refereed]

     View Summary

    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.

  • 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     639 - 643  2005  [Refereed]

     View Summary

    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.

  • 『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  2004.09

    CiNii

  • 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  2004.05

    CiNii

  • 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  [Refereed]

     View Summary

    In this study, we propose and develop an open-source groupware system called NetIsle. NetIsle is a general-purpose groupware system for uniform open groups that integrate a number of tools for online collaboration to ensure fast information exchange and sharing, increase the productivity of working groups, and reduce maintenance and administration costs. The main technologies used for the construction of the system are peer-to-peer (P2P) and push, which are best fitted to those principles and beliefs we build our system upon.

  • 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     183 - 188  2004  [Refereed]

     View Summary

    This paper presents a multi-agent system to assist a teacher managing his/her course contents placed on web servers. In this system there is a set of agents and every agent may work independently from or collaboratively with others. Once generated, an agent can reside in a teacher's daily working computer (called administration host) or a proxy host, and can move between the two hosts. Each agent is devoted to one piece of job and all of them, as a whole, coordinately conduct a sequence of management work during the entire process of teaching a course. A teacher may administrate agents via a specific system shell on his/her administration host, or a usual web browser on another computer/PDA/mobile phone. The system has been carefully modularized, and thus a new type of agent, if necessary, can be relatively easily developed and quickly incorporated into the system to further enhance or extend its management capability.

  • 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  [Refereed]

     View Summary

    This paper describes small group collaboration solutions based upon push technology, which provides awareness for collaboration, reduces efforts for necessary information discovery, and makes users collaboration initiators, active information providers and new values creators. The push technology-based tools, i.e. File Pusher, Scheduler, NetIsle Mailer, etc., axe implemented in a hybrid peer-to-peer general-purpose groupware system, called NetIsle, which has been developed by using Java RMI and sockets and can be run on any platform where Java VM is available.

  • Individualized collaboration support for online leaning communities

    Q Jin

    INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, VOLS I AND II, PROCEEDINGS     784 - 788  2002  [Refereed]

     View Summary

    In this paper we introduce a framework for every-netizen online learning communities that widely open to anyone who is willing to learn and share knowledge with others across the networks. We discuss how to provide individualized collaboration support for e-learning in the community, and demonstrate a prototype of implementation in a web-based social virtual environment with two supporting tools.

  • 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  [Refereed]

     View Summary

    As a new distributed computing paradigm, peer-to-peer (P2P) networks and systems have attracted more and more attentions in recent years. This study aims at proposing and constructing a new information resource sharing system based on the P2P paradigm. In this paper, we focus on solving and improving the hit rate and search speed problems that exist in Gnutella, one of the most popular P2P file sharing systems. We discuss how to introduce XML to describe the attributes and properties of each shared file and integrate an embedded database engine to increase the search speed. Preliminary experiment results have demonstrated that the approach proposed in this study is efficient and useful.

  • Computer supported social networking for augmenting cooperation

    H. Ogata, Y. Yano, N. Furugori, Q. Jin

    Computer Supported Cooperative Work   10 ( 2 ) 189 - 209  2001  [Refereed]

     View Summary

    The exploration of social networks is essential for finding capable cooperators who can help problem-solving and for augmenting cooperation between workers in an organization. This paper describes PeCo-Mediator-II to seek capable cooperators through a chain of personal connections (PeCo) in a networked organization. Moreover, this system helps to gather, explore, and visualize social networks in an organization. The experimental results show that the system facilitates users' encounters with cooperators and develops new helpful connections with the cooperators.

    DOI

  • Design of a virtual community based interactive learning environment

    Q Jin

    PROCEEDINGS OF THE FIFTH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1 AND 2     A636 - A642  2000  [Refereed]

     View Summary

    In this paper, we propose a conceptual framework for every-citizen learning comminities based on a recently widespread Internet tool known as MOO (Multi user dimension Object-Oriented). We discuss the design and development of a prototype system of virtual community based interactive learning environments, which supports human-human communication in addition to human-computer communication, with emphsis on social interaction.

  • Proposal and Experiment of Supporting Social Networks Exploration with Past Results(<Special Issue>Human Interface and Interaction)

    Ogata Hiroaki, Yano Yoneo, Furugori Nobuko, Jin Qun

    IPSJ Journal   40 ( 2 ) 632 - 641  1999.02  [Refereed]

     View Summary

    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

  • PeCo-Mediator-II:Supporting to Find Partner(s) through Personal Connections in a Networked Environment

    OGATA Hiroaki, FURUGORI Nobuko, JIN Qun, YANO Yoneo

    The transactions of the Institute of Electronics, Information and Communication Engineers   80 ( 7 ) 551 - 560  1997.07  [Refereed]

    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  [Refereed]

     View Summary

    Petri nets can be viewed as a kind of language for specifying Markov models of a system, because of their highly visual nature that can give insight into the nature of the modeled system. In this paper, an aggregate approach by extended stochastic Petri net and Markov renewal process with some non-regeneration points is proposed to conduct performance analysis of an Ethernet-based flexible manufacturing system. The proposed approach may improve efficiency of performance analysis for most practical distributed network based manufacturing systems.

  • 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  [Refereed]

     View Summary

    In the past few years, a network-accessible, multi-user simulated environment known as MUD has becoming widespread on the Internet for purposes of entertainment and education. In this paper, we firstly discuss design issues of collaborative learning in text-based virtual reality environments. We describe our experimental MUD based virtual learning environment, its integration with outside databases and Internet resources, and a graphical user interface to use it. Finally, we introduce our experimental use of this virtual learning environment, experiences from having virtual lessons in it, and some primary evaluation results.

  • 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  1996.11  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    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     187 - 192  1996  [Refereed]

     View Summary

    When interacting and acting in a dynamic multiagent environment, an agent must ask itself what is presently its best course of action given what it now knows about what the environment will be like when it intends to act. It requires some ability to make decision by computing the probability that relevant propositions will hold at a specified point of time. Among the interaction and action, some of them can be characterized by an exponential time distribution, others might not. This paper presents a non-regenerative stochastic Petri net that allows arbitrary time distributions, use it to model and analyze agents' probabilistic behavior.

  • 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  [Refereed]

     View Summary

    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

     View Summary

    In this paper, we describe the distributed PeCo-Mediator which support a user to find a partner by using personal connections (PeCo). We have already proposed PeCo-Mediator which allows members to share and use their PeCo. PeCo-Mediator is very available in some small groups. In an organizational use, however, there are some problems; (1) It is difficult a user to offer his/her ties because they are private information; (2) Since this system only supports to find some candidate partners and relationships with them, a user has to negotiate with them to get the cooperation, using the offered connection. Distributed PeCo-Mediator has the two sub-systems; PeCo-Collector for maintaining the individual PeCo in his/her own site, and PeCo-Agent for supporting the negotiation between him/her and a candidate. It improves the privacy of users and also facilitates to find a cooperative and capable partner.

  • 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

     View Summary

    This paper describes COMES (Collaborative Organizational Memory System) for supporting real-time collaboration in organizational problem solving. A related area of research investigates organizational memory or know-how systems such as Answer Garden and FISH. These systems are generally text-based and asynchronous. However, users must often repeat to exchange question and answer with each other to solve a problem; and only text-based information makes it difficult for them to communicate smoothly. Therefore, COMES allows organizational members to collaborate with each other in synchronous text-and-sketch based problem-solving forums connected via the Internet and makes its process retrievable and visible.

  • PeCo-Mediator:Development and Modelling of a Supporting System for Sharing and Handling Personal Connections

    Ogata Hiroaki, Yano Yoneo, Furugori Nobuko, Jin Qun

    IPSJ Journal   36 ( 6 ) 1299 - 1309  1995.06  [Refereed]

     View Summary

    A PeCo(Personal Connection) is often a starting point for business activities. This paper describes : 1)PeCo-Mediator, which facilitates access to others who can help problem solving in business activities by sharing and using wide ranges PeCos beyond individuals, 2)its flexible database which has a flexible data-structure and key concepts &quot;flexibility and adaptability&quot;, 3)a model of PeCos. The flexible database allows users to store their diverse personal information and to easily find people who can help solve their business problems. Use of shared PeCos through PeCo-Mediator facilitates ...

    CiNii

  • 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  [Refereed]

    DOI

  • 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  1994.09  [Refereed]

     View Summary

    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

▼display all

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 )  2008.11

    CiNii

  • Database Agents for Collaborative Learning in Virtual Environments

    JIN Qun, OGATA Hiroaki, YANO Yoneo

    全国大会講演論文集   55 ( 3 ) 298 - 299  1997.09

     View Summary

    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

  • A Collaborative Learning Enviroment Using a Text-Based Virtual Reality System

    SHIRAKUSA Yoshihiro, SHAO Yingzhi, JIN Qun, TANO Yoneo

      1996 ( 2 ) 3 - 8  1996.09

    CiNii

  • Development of a Supporting System for Group Use of Personal Connections Using Collaborative Agents.

    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  1996.05

     View Summary

    Recently, the internet makes it ver easy and convenient for various kinds of experts to communicate with each other and they form a knowledgeable network. We consider their personal connections (PeCo) to be the network and investigate the way to use the network for their problem solving. We expect that the users can obtain excellent results by integrating their ideas through the network. This paper describes PeCo-Collector which gathers and manages their respective PeCo, and PeCo-Agent which searches cooperative and capable partner(s) in the network.

    CiNii J-GLOBAL

  • Development of a Japanese Mimesis and Onomatopoeia Dictionary System for Foreigners.

    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  1996.03

     View Summary

    This paper describes the development of a Japanese mimesis and onomatopoeia dictionary system called JAMIOS. Mimesis and onomatopoeia tend to be used frequently in Japan. However, they are words that express diverse feelings particular to the Japanese culture. Therefore, it is difficult for foreigniers to understand mimesis and onomatopoeia. We focus on the situation, pronunciation, meaning, usage and feeling. JAMIOS has the following features : (1)The system presents the situation using multi media, and the user can advance the search by changing the situation or the pronunciation. (2)Users can search knowledge or related words along the feature of mimesis and onomatopoeia. (3)The system presents the usage of Japanese using example sentences.

    CiNii J-GLOBAL

  • Development of a Japanese Polite Expressions CAI system

    MURATA Rie, OCHI Youji, AYALA Gerardo, OGATA Hiroaki, JIN Qun, YANO Yoneo, HAYASHI Toshihiro, NOMURA Chieko, KOUNO Nayoko

    IEICE technical report. Education technology   95 ( 604 ) 41 - 48  1996.03

     View Summary

    When foreigners who study Japanese are used to the language, they find some difficulties with polite expressions. For instance, they can&#039;t make themselves fully understand in Japanese because of the different point of views between the Japanese people and the student. It causes a change in the complexity of polite expressions because of a change in the situation or in the personal relations. Foreigners have problems in the use of polite expressions when (1)they don&#039;t understand the personal relations in Japan. (2)they don&#039;t understand the suitable polite expressions for a situation accordin...

    CiNii J-GLOBAL

  • Development of a Japanese Onomatopoeia and Mimesis Dictionary System for Foreigners.

    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  1995.08

    J-GLOBAL

  • Development of a Japanese Honorific Expressions CAI System with Consideration of Personal Relations.

    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  1995.08

    J-GLOBAL

  • Construction of mimetic word and imitation sound word dictionary system for foreigners.

    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

    J-GLOBAL

  • Modeling of human connection search agent in human connection utilization support system.

    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

    J-GLOBAL

  • PeCo-Collector: Human connection database system in internet environment.

    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

    J-GLOBAL

  • Construction of Japanese respect expression learning support system considering personal relations.

    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

    J-GLOBAL

  • Construction of ORMEX, a joint ownership system of know-how based on case examples.

    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

    J-GLOBAL

  • Flexible‐structured framework for handling nonstandard information.Connection utilization support system.

    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

    J-GLOBAL

  • Development of a supporting system for practical use of personal connections : Personal information sharing and handling environment

    Ogata Hiroaki, Morikawa Tomiaki, Yano Yoneo, Furugori Nobuko, Jin Qun

    IPSJ SIG Notes   93 ( 95 ) 29 - 36  1993.10

     View Summary

    A new project is often promoted and a negotiation is often concluded by using various fields and many personal connections (PeCo) positively. This system aims to share and use PeCo that each group member obtains in her/his social relationships. Generally it is difficult for traditional database systems to share and handle dynamic, ill-formed and private data such as PeCo. This paper describes an environment which clears up this problem. This environment supports users allowing them to share private and ill-formed information, the database of this system evolves in proportion to its use.

    CiNii

  • Development of a supporting system for practical use of personal connections.

    緒方広明, 森川富昭, 林敏浩, 矢野米雄, 土定正明, 古郡延子, JIN Qun

    情報処理学会研究報告   93 ( 56(GW-2) ) 57 - 64  1993.06

     View Summary

    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&#039; 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

▼display all

Other

  • https://nislab.human.waseda.ac.jp/

  • https://waseda.pure.elsevier.com/en/persons/qun-jin/publications/

  • http://www.f.waseda.jp/jin/

Research Projects

  • Empowering the life style and wellbeing of eastern Asian elders with intelligent IoT

    JSPS  A3 Foresight Program

    Project Year :

    2020.08
    -
    2025.07
     

    Jin Nakazawa

  • E-Inclusion: Creating Accessible Local/Social Services for People with Disabilities

    Japan Science and Technology Agency (JST)  Solution-Driven Co-creative R&D Program for SDGs (SOLVE for SDGs)

    Project Year :

    2019.11
    -
    2021.10
     

    Mamoru Iwabuchi

  • Fundamental Health Control Model Based on Integrated Analysis of Life Logs and Pulse Data toward Holistic Living Support for the Elderly

    Masaru Ibuka Foundation  Human Sciences Research Project on Oriental Medicine

    Project Year :

    2016.04
    -
    2019.03
     

    Qun Jin

  • Fundamental Models and Mechanisms for Sustainable Use of Personal Big Data

    Waseda University  Grants for Special Research Projects

    Project Year :

    2014.04
    -
    2015.03
     

    Qun Jin

  • Development of Distributed Collaborative Knowledge and Information Sharing Systems as the Foundation of Growing Campus

    Waseda University  Advanced Research Center for Human Sciences Seeds-Type Research Project

    Project Year :

    2010.04
    -
    2013.03
     

    Shoji Nishimura

  • Integration of Real-World Experiment, Practice and Experience with Ubiquitous Learning

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (A)

    Project Year :

    2007.04
    -
    2010.03
     

    Yoneo Yano

  • Development of Human-Centric Distributed Collaborative Knowledge and Information Sharing Systems and Applications at E-School

    Waseda University  Advanced Research Center for Human Sciences Seeds-Type Research Project

    Project Year :

    2004.04
    -
    2007.03
     

    Qun Jin

  • Development of a New Learning Community Model for Higher Education Using Broadband Networks

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2003.04
    -
    2007.03
     

    Chiharu Kogo

  • Learning Communities Using Virtual Reality Environment Media

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2000.04
    -
    2003.03
     

    Qun Jin

  • Development of Agent-based Collaborative Learning Support Systems focusing on Social Networks

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    2000.04
    -
    2002.03
     

    Hiroaki Ogata

  • Development of Flexible Collaborative Learning Environments for Japanese Language Instruction Using Agents

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    1997.04
    -
    2001.03
     

    Yoneo Yano

  • Development of Multimedia Dictionay for Japanese Language Learning on Internet

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research (B)

    Project Year :

    1997.04
    -
    2001.03
     

    Yoneo yano

  • Text-Based Virtual Reality for Collaborative Learning Support

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Encouragement of Scientists (A)

    Project Year :

    1998.04
    -
    2000.03
     

    Qun Jin

  • Development of Active Database Systems for Collaborative Learning

    Japan Society for the Promotion of Science (JSPS)  Grant-in-Aid for Scientific Research on Priority Areas

    Project Year :

    1997.04
    -
    1998.03
     

    Yoneo Yano

▼display all

Specific Research

  • 個人モデルに基づくヘルスデータの縦横比較分析

    2021  

     View Summary

    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。

  • 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  

     View Summary

    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。

  • 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  

     View Summary

    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。

  • 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  

     View Summary

    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  

     View Summary

    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  

     View Summary

     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   武 博

     View Summary

    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  

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    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  

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    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   周 暁康

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    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  

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     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  

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     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   シュティフ ロマン

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     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   シュティフ ロマン

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     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   シュティフ ロマン

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     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。

  • 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  

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     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

    2005  

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     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。

  • 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  

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     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  

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     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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Overseas Activities

  • 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

    2012.03
    -
    2013.03

    中国   中国計量学院、北京大学、上海大学

 

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