User model-based information filtering

  • Fabio A. Asnicar
  • Massimo Di Fant
  • Carlo Tasso
Knowledge Representation 1
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1321)


The IFT (Information Filtering Tool) project has the goal of developing new approaches to information filtering which are based on user modeling techniques for building and managing the representation of the user information preferences. In this paper we describe three prototypes which have been developed and evaluated within the project. All of them are dealing with textual semistructured documents and exploit a semantic network representation of user preferences: the first two prototypes (IFTool and PIFT) are characterized by two different matching algorithms utilized for assessing the relevance of an incoming document against the user model, whereas the third (ifWeb) concerns an application of IFTool to the navigation and filtering of documents in the INTERNET. The three prototypes have been evaluated in order to compare their performance with similar systems presented in the literature. The results achieved show that information filtering can positively profit from user modeling techniques, and point out interesting challenges for future investigations.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Fabio A. Asnicar
    • 1
  • Massimo Di Fant
    • 1
  • Carlo Tasso
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of UdineUdineItaly

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