Personal Data Analytics to Facilitate Cyber Individual Modeling

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

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルProceedings - 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 2016 IEEE 14th International Conference on Pervasive Intelligence and Computing, PICom 2016, 2016 IEEE 2nd International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ39-46
    ページ数8
    ISBN(電子版)9781509040650
    DOI
    出版ステータスPublished - 2016 10 11
    イベント14th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 14th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2016, 2nd IEEE International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016 - Auckland, New Zealand
    継続期間: 2016 8 82016 8 10

    Other

    Other14th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 14th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2016, 2nd IEEE International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
    国/地域New Zealand
    CityAuckland
    Period16/8/816/8/10

    ASJC Scopus subject areas

    • コンピュータ ビジョンおよびパターン認識
    • 情報システム
    • コンピュータ サイエンス(その他)
    • 人工知能
    • コンピュータ ネットワークおよび通信

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