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Ordinal Association Rules towards Association Rules

  • Sylvie Guillaume
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2737)

Abstract

Intensity of inclination, an objective rule-interest measure, allows us to extract implications on databases without having to go through the step of transforming the initial set of attributes into binary attributes, thereby avoiding obtaining a prohibitive number of rules of little significance with many redundancies. This new kind of rule, ordinal association rules, reveals the overall behavior of the population and it is vital that this study be extended by exploring specific ordinal association rules in order to refine our analysis and to extract behaviors in sub-sets. This paper focuses on the mining of association rules based on extracted ordinal association rules in order to, on the one hand remove the discretization step of numeric attributes and the step of complete disjunctive coding, and on the other hand obtain a variable discretization of numeric attributes i.e. dependent on association of attributes. The study ends with an evaluation of an application to some banking data.

Keywords

Association rules interestingness measures implicative analysis and numeric attributes 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sylvie Guillaume
    • 1
  1. 1.Laboratoire LIMOS, UMR 6158 CNRSUniversité Blaise Pascal, Complexe scientifique des CézeauxAUBIERE CedexFrance

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