Fuzzy Bayesian Classifier: a Multi-Agent System for Information Retrieval in the Web

  • José C. Romero Cortés
  • Leonid B. Sheremetov
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 19)


A fuzzy Bayesian approach helping an Internet user to filter Web pages is discussed. In the proposed approach, one page can be classified as having the continuous quality of being interesting, this means that a certain grade of membership can be associated with each page relative to a category of selection. Filtering is based on the evidences of the content of the page title, abstract or complete document. An example comparing crisp and fuzzy classifiers implemented as a part of multi-agent system to support information filtering and retrieval in the Web is discussed illustrating the proposed approach.


Posteriori Probability Page Title Agent Platform Fuzzy Classifier Search Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • José C. Romero Cortés
    • 1
    • 2
  • Leonid B. Sheremetov
    • 1
    • 3
  1. 1.Center for Computing Research of the National Technical University, (CICIPN)Mexico, D.F.
  2. 2.Metropolitan Autonomous UniversityAcapotzalcoMexico, D.F.
  3. 3.Mexican Oil InstituteMexico DF.

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