Context mining and integration into predictive web analytics

Y. Kiseleva

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Downloads (Pure)


    Predictive Web Analytics is aimed at understanding behavioural patterns of users of various web-based applications: e-commerce, ubiquitous and mobile computing, and computational advertising. Within these applications business decisions often rely on two types of predictions: an overall or particular user segment demand predictions and individualised recommendations for visitors. Visitor behaviour is inherently sensitive to the context, which can be defined as a collection of external factors. Context-awareness allows integrating external explanatory information into the learning process and adapting user behaviour accordingly. The importance of context-awareness has been recognised by researchers and practitioners in many disciplines, including recommendation systems, information retrieval, personalisation, data mining, and marketing. We focus on studying ways of context discovery and its integration into predictive analytics.
    Original languageEnglish
    Title of host publication22nd International Conference on World Wide Web Companion (WWW '13 Companion, Rio de Janeiro, Brazil, May 13-17, 2013)
    Place of PublicationNew York NY
    PublisherAssociation for Computing Machinery, Inc
    ISBN (Print)978-1-4503-2038-2
    Publication statusPublished - 2013


    Dive into the research topics of 'Context mining and integration into predictive web analytics'. Together they form a unique fingerprint.

    Cite this