BIROn - Birkbeck Institutional Research Online

    Computing the entropy of user navigation in the web

    Levene, Mark and Loizou, George (2003) Computing the entropy of user navigation in the web. International Journal of Information Technology and Decision Making 2 (3), pp. 459-476. ISSN 0219-6220.

    [img]
    Preview
    Text
    entropy.pdf

    Download (226kB) | Preview

    Abstract

    Navigation through the web, colloquially known as "surfing", is one of the main activities of users during web interaction. When users follow a navigation trail they often tend to get disoriented in terms of the goals of their original query and thus the discovery of typical user trails could be useful in providing navigation assistance. Herein, we give a theoretical underpinning of user navigation in terms of the entropy of an underlying Markov chain modelling the web topology. We present a novel method for online incremental computation of the entropy and a large deviation result regarding the length of a trail to realize the said entropy. We provide an error analysis for our estimation of the entropy in terms of the divergence between the empirical and actual probabilities. We then indicate applications of our algorithm in the area of web data mining. Finally, we present an extension of our technique to higher-order Markov chains by a suitable reduction of a higher-order Markov chain model to a first-order one.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): Web user navigation, web data mining, navigation problem, Markov chain, entropy
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Administrator
    Date Deposited: 23 Aug 2005
    Last Modified: 09 Aug 2023 12:28
    URI: https://eprints.bbk.ac.uk/id/eprint/212

    Statistics

    Activity Overview
    6 month trend
    650Downloads
    6 month trend
    408Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item
    Edit/View Item