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International Conference on User Modeling

UM 2003: User Modeling 2003 pp 55–64Cite as

Adapting to the User’s Internet Search Strategy

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2702))

Abstract

World Wide Web search engines typically return thousands of results to the users. To avoid users browsing through the whole list of results, search engines use ranking algorithms to order the list according to predefined criteria. In this paper, we present Toogle, a front-end to the Google search engine for both desktop browsers and mobile phones. For a given search query, Toogle first ranks results using Google’s algorithm and, as the user browses through the result list, uses machine learning techniques to infer a model of her search goal and to adapt accordingly the order in which the results are presented. We describe preliminary experimental results that show the effectiveness of Toogle.

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Author information

Authors and Affiliations

  1. e-lab Bouygues SA, 1avenue Eugène Freyssinet, 78061, St Quentin en Yvelines, France

    Jean-David Ruvini

Authors
  1. Jean-David Ruvini
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Editor information

Editors and Affiliations

  1. School of Information Sciences, Department of Information Science and Telecommunications, University of Pittsburgh, 135 North Bellefield Avenue, Pittsburgh, PA, 15260, USA

    Peter Brusilovsky

  2. Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Albert Corbett

  3. Intelligent Interfaces, Department of Informatics, University of Bari, Via Orabona 4, 70126, Bari, Italy

    Fiorella de Rosis

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© 2003 Springer-Verlag Berlin Heidelberg

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Ruvini, JD. (2003). Adapting to the User’s Internet Search Strategy. In: Brusilovsky, P., Corbett, A., de Rosis, F. (eds) User Modeling 2003. UM 2003. Lecture Notes in Computer Science(), vol 2702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44963-9_9

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  • DOI: https://doi.org/10.1007/3-540-44963-9_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40381-4

  • Online ISBN: 978-3-540-44963-8

  • eBook Packages: Springer Book Archive

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