A web recommender system based on dynamic sampling of user information access behaviors

Jian Chen, Roman Y. Shtykh, Qun Jin

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

    2 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009
    Pages172-177
    Number of pages6
    Volume2
    DOIs
    Publication statusPublished - 2009
    EventIEEE 9th International Conference on Computer and Information Technology, CIT 2009 - Xiamen
    Duration: 2009 Oct 112009 Oct 14

    Other

    OtherIEEE 9th International Conference on Computer and Information Technology, CIT 2009
    CityXiamen
    Period09/10/1109/10/14

    Fingerprint

    Recommender systems
    Sampling

    Keywords

    • Data mining
    • Dynamic sampling
    • Gradual adaption
    • Information recommendation
    • Wikipedia

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Science Applications
    • Hardware and Architecture
    • Software

    Cite this

    Chen, J., Shtykh, R. Y., & Jin, Q. (2009). A web recommender system based on dynamic sampling of user information access behaviors. In Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009 (Vol. 2, pp. 172-177). [5329111] https://doi.org/10.1109/CIT.2009.119

    A web recommender system based on dynamic sampling of user information access behaviors. / Chen, Jian; Shtykh, Roman Y.; Jin, Qun.

    Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009. Vol. 2 2009. p. 172-177 5329111.

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

    Chen, J, Shtykh, RY & Jin, Q 2009, A web recommender system based on dynamic sampling of user information access behaviors. in Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009. vol. 2, 5329111, pp. 172-177, IEEE 9th International Conference on Computer and Information Technology, CIT 2009, Xiamen, 09/10/11. https://doi.org/10.1109/CIT.2009.119
    Chen J, Shtykh RY, Jin Q. A web recommender system based on dynamic sampling of user information access behaviors. In Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009. Vol. 2. 2009. p. 172-177. 5329111 https://doi.org/10.1109/CIT.2009.119
    Chen, Jian ; Shtykh, Roman Y. ; Jin, Qun. / A web recommender system based on dynamic sampling of user information access behaviors. Proceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009. Vol. 2 2009. pp. 172-177
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