Mining Fuzzy Quantitative Association Rules

  • Authors:
  • Weining Zhang

  • Affiliations:
  • -

  • Venue:
  • ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
  • Year:
  • 1999

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Abstract

Given a relational database and a set of fuzzy terms defined for some attributes, we consider the problem of mining fuzzy quantitative association rules that may contain crisp values, intervals, and fuzzy terms in both antecedent and consequent. We present an algorithm extended from the equi-depth partition (EDP) algorithm for solving this problem. Our approach combines interval partition with pre-defined fuzzy terms and is more general.