Learning links between a user’s calendar and information needs

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

    1 Citation (Scopus)


    Personal information needs depend on long-term interests and on current and future situations (contexts): people are mainly interested in weather forecasts for future destinations, and in toy advertisements when a child’s birthday approaches. As computer capabilities for being aware of users’ contexts grow, the users’ willingness to set manually rules for context-based information retrieval will decrease. Thus computers must learn to associate user contexts with information needs in order to collect and present information proactively. This work presents experiments with training a SVM (Support Vector Machines) classifier to learn user information needs from calendar information.
    Original languageEnglish
    Title of host publicationAdvances in Information Retrieval
    Subtitle of host publicationProceedings of ECIR 2006
    EditorsM. Lalmas, A. MacFarlane, S. Rüger, A. Tombros, T. Tsikrika, A. Yavlinsky
    ISBN (Electronic)978-3-540-33348-7
    ISBN (Print)978-3-540-33347-0
    Publication statusPublished - 2006
    MoE publication typeA4 Article in a conference publication
    Event28th European Conference on IR Research, ECIR 2006 - London, United Kingdom
    Duration: 10 Apr 200612 Apr 2006

    Publication series

    SeriesLecture Notes in Computer Science


    Conference28th European Conference on IR Research, ECIR 2006
    Abbreviated titleECIR 2006
    Country/TerritoryUnited Kingdom


    • SVM
    • support vector machines
    • context-based information retrieval
    • user information needs


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