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Improving User Modelling with Content-Based Techniques

  • Bernardo Magnini
  • Carlo Strapparava
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)

Abstract

SiteIF is a personal agent for a bilingual news web site that learns user’s interests from the requested pages.

In this paper we propose to use a content-based document representation as a starting point to build a model of the user’s interests. Documents passed over are processed and relevant senses (disambiguated over WORDNET) are extracted and then combined to form a semantic network. A filtering procedure dynamically predicts new documents on the basis of the semantic network.

There are two main advantages of a content-based approach: first, the model predictions, being based on senses rather then words, are more accurate; second, the model is language independent, allowing navigation in multilingual sites. We report the results of a comparative experiment that has been carried out to give a quantitative estimation of these improvements.

Keywords

Content-Based User Modelling Natural Language Processing WORDNET 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Bernardo Magnini
    • 1
  • Carlo Strapparava
    • 1
  1. 1.ITC-irst, Istituto per la Ricerca Scientifica e TecnologicaTrentoItaly

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