User correlation discovery and dynamical profiling based on social streams

Xiaokang Zhou, Qun Jin

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

    7 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages53-62
    Number of pages10
    Volume7669 LNCS
    DOIs
    Publication statusPublished - 2012
    Event8th International Conference on Active Media Technology, AMT 2012 - Macau
    Duration: 2012 Dec 42012 Dec 7

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume7669 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other8th International Conference on Active Media Technology, AMT 2012
    CityMacau
    Period12/12/412/12/7

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    Keywords

    • Information Seeking
    • SNS
    • Social Stream
    • Stream Metaphor
    • User Profiling

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Zhou, X., & Jin, Q. (2012). User correlation discovery and dynamical profiling based on social streams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7669 LNCS, pp. 53-62). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7669 LNCS). https://doi.org/10.1007/978-3-642-35236-2_6