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Creating a Fuzzy Believer to Model Human Newspaper Readers

  • Ralf Krestel
  • René Witte
  • Sabine Bergler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4509)

Abstract

We present a system capable of modeling human newspaper readers. It is based on the extraction of reported speech, which is subsequently converted into a fuzzy theory-based representation of single statements. A domain analysis then assigns statements to topics. A number of fuzzy set operators, including fuzzy belief revision, are applied to model different belief strategies. At the end, our system holds certain beliefs while rejecting others.

Keywords

Natural Language Processing Newspaper Article Sentence Pair Fuzzy Processing Intelligent Data Analysis 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Ralf Krestel
    • 1
  • René Witte
    • 1
  • Sabine Bergler
    • 2
  1. 1.Institut für Programmstrukturen und Datenorganisation (IPD), Universität Karlsruhe (TH)Germany
  2. 2.Department of Computer Science and Software Engineering, Concordia University, MontréalCanada

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