Time based segmentation of log data for user navigation prediction in personalization

M Halvey, M T Keane, B Smyth

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

    Abstract

    There are many systems that attempt to predict user navigation on the Internet through the use of past behavior, preferences and environmental factors. We believe that many of these models have shortcomings, in that they do not take into account that users may have many different sets of preferences, specifically, we investigate time as an environmental factor in making predictions about user navigation. We present a method for segmenting log files in order to learn time dependent models to predict user navigation patterns and show the benefits of these models over traditional methods. An analysis is carried out on a sample of usage logs for Wireless Application Protocol (WAP) browsing, and the results of this analysis verify our hypothesis.
    Original languageEnglish
    Title of host publicationThe 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)
    PublisherIEEE
    Pages636-640
    Number of pages5
    ISBN (Print)076952415X
    DOIs
    Publication statusPublished - 17 Oct 2005

    Keywords

    • WAP
    • portals
    • pattern analysis
    • navigation
    • internet

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  • Cite this

    Halvey, M., Keane, M. T., & Smyth, B. (2005). Time based segmentation of log data for user navigation prediction in personalization. In The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05) (pp. 636-640). IEEE. https://doi.org/10.1109/WI.2005.147