A Discussion of Indices for the Evaluation of Fuzzy Associations in Relational Databases

  • Didier Dubois
  • Henri Prade
  • Thomas Sudkamp
Conference paper

DOI: 10.1007/3-540-44967-1_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2715)
Cite this paper as:
Dubois D., Prade H., Sudkamp T. (2003) A Discussion of Indices for the Evaluation of Fuzzy Associations in Relational Databases. In: Bilgiç T., De Baets B., Kaynak O. (eds) Fuzzy Sets and Systems — IFSA 2003. IFSA 2003. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), vol 2715. Springer, Berlin, Heidelberg

Abstract

This paper investigates techniques to identify and evaluate associations in a relational database that are expressed by fuzzy if-then rules. Extensions of the classical confidence measure based on the α-cut decompositions of the fuzzy sets are proposed to address the problems associated with the normalization in scalar-valued generalizations of confidence. An analysis by α-level differentiates strongly and weakly supported associations and identifies robustness in an association. In addition, a method is proposed to assess the validity of a fuzzy association based on the ratio of examples to counterexamples.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Didier Dubois
    • 1
  • Henri Prade
    • 1
  • Thomas Sudkamp
    • 2
  1. 1.IRIT-CNRSUniversité Paul SabatierToulouseFrance
  2. 2.Dept. of Computer ScienceWright State UniversityDaytonUSA

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