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Intelligent Information Access by Learning WordNet-Based User Profiles

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AI*IA 2005: Advances in Artificial Intelligence (AI*IA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3673))

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Abstract

The central argument of this paper the induction user profiles by supervised machine learning techniques for Intelligent Information Access. The access must be highly personalized by user profiles, in which representations of the users’ interests are maintained. Moreover, users want to retrieve information on the basis of conceptual content, but individual words provide unreliable evidence about the content of documents. A possible solution is the adoption of WordNet as a lexical resource to induce semantic user profiles.

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References

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Authors and Affiliations

  1. Dipartimento di Informatica, Università di Bari, Via E. Orabona, 4, 70125, Bari, Italia

    M. Degemmis, P. Lops & G. Semeraro

Authors
  1. M. Degemmis
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  2. P. Lops
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  3. G. Semeraro
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Editors and Affiliations

  1. Research Center on Complex Systems and Artificial Intelligence (CSAI) Department of Computer Science, Systems and Communication (DISCo), University of Milan, Bicocca viale Sarca, 336, 20126, Milan, (Italy)

    Stefania Bandini

  2. CSAI - Complex Systems & Artificial Intelligence Research Centre, University of Milano–Bicocca,  

    Sara Manzoni

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© 2005 Springer-Verlag Berlin Heidelberg

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Degemmis, M., Lops, P., Semeraro, G. (2005). Intelligent Information Access by Learning WordNet-Based User Profiles. In: Bandini, S., Manzoni, S. (eds) AI*IA 2005: Advances in Artificial Intelligence. AI*IA 2005. Lecture Notes in Computer Science(), vol 3673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558590_8

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  • DOI: https://doi.org/10.1007/11558590_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29041-4

  • Online ISBN: 978-3-540-31733-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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