Gradual adaption model for estimation of user information access behavior

Jian Chen, Roman Y. Shtykh, Qun Jin

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

    1 Citation (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProc. - 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
    Pages378-383
    Number of pages6
    DOIs
    Publication statusPublished - 2008
    Event3rd International Conference on Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services - Sliema
    Duration: 2008 Oct 262008 Oct 31

    Other

    Other3rd International Conference on Systems and Networks Communications, ICSNC 2008 - Includes I-CENTRIC 2008: International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services
    CitySliema
    Period08/10/2608/10/31

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Control and Systems Engineering

    Cite this

    Chen, J., Shtykh, R. Y., & Jin, Q. (2008). Gradual adaption model for estimation of user information access behavior. In 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 (pp. 378-383). [4693700] https://doi.org/10.1109/ICSNC.2008.56