Using Intuitionistic Fuzzy Sets in Text Categorization

  • Authors:
  • Eulalia Szmidt;Janusz Kacprzyk

  • Affiliations:
  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland 01---447;Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland 01---447

  • Venue:
  • ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
  • Year:
  • 2006

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Abstract

We address some crucial problem associated with text categorization, a local feature selection. It seems that intuitionistic fuzzy sets can be an effective and efficient tool making it possible to assess each term (from a feature set for each category) from a point of view of both its indicative and non-indicative ability. It is important especially for high dimensional problems to improve text filtering via a confident rejection of non-relevant documents. Moreover, we indicate that intuitionistic fuzzy sets are a good tool for the classification of imbalanced and overlapping classes, a commonly encountered case in text categorization.