Personal Data Analytics to Facilitate Cyber Individual Modeling

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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings - 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
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages39-46
    Number of pages8
    ISBN (Electronic)9781509040650
    DOIs
    Publication statusPublished - 2016 Oct 11
    Event14th 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
    Duration: 2016 Aug 82016 Aug 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
    CountryNew Zealand
    CityAuckland
    Period16/8/816/8/10

    Fingerprint

    Data privacy
    Mobile computing
    Software agents
    Ubiquitous computing
    Information management

    Keywords

    • Cyber-I
    • Data Analysis
    • Social Networking Service
    • User Modeling
    • Web Mining

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Information Systems
    • Computer Science (miscellaneous)
    • Artificial Intelligence
    • Computer Networks and Communications

    Cite this

    Zhou, X., Wu, B., Jin, Q., Ma, J., Li, W., & Yen, N. Y. (2016). Personal Data Analytics to Facilitate Cyber Individual Modeling. In 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 (pp. 39-46). [7588817] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.22

    Personal Data Analytics to Facilitate Cyber Individual Modeling. / Zhou, Xiaokang; Wu, Bo; Jin, Qun; Ma, Jianhua; Li, Weimin; Yen, Neil Y.

    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. Institute of Electrical and Electronics Engineers Inc., 2016. p. 39-46 7588817.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Zhou, X, Wu, B, Jin, Q, Ma, J, Li, W & Yen, NY 2016, Personal Data Analytics to Facilitate Cyber Individual Modeling. in 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., 7588817, Institute of Electrical and Electronics Engineers Inc., pp. 39-46, 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, 16/8/8. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.22
    Zhou X, Wu B, Jin Q, Ma J, Li W, Yen NY. Personal Data Analytics to Facilitate Cyber Individual Modeling. In 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. Institute of Electrical and Electronics Engineers Inc. 2016. p. 39-46. 7588817 https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.22
    Zhou, Xiaokang ; Wu, Bo ; Jin, Qun ; Ma, Jianhua ; Li, Weimin ; Yen, Neil Y. / Personal Data Analytics to Facilitate Cyber Individual Modeling. 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. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 39-46
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