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Mining Clusters with Association Rules

  • Walter A. Kosters
  • Elena Marchiori
  • Ard A. J. Oerlemans
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1642)

Abstract

In this paper we propose a method for extracting clusters in a population of customers, where the only information available is the list of products bought by the individual clients. We use association rules having high confidence to construct a hierarchical sequence of clusters. A specific metric is introduced for measuring the quality of the resulting clusterings. Practical consequences are discussed in view of some experiments on real life datasets.

Keywords

Association Rule Support Threshold Apriori Algorithm Minimum Support Threshold Binary Attribute 
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-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Walter A. Kosters
    • 1
  • Elena Marchiori
    • 1
  • Ard A. J. Oerlemans
    • 1
  1. 1.Leiden Institute of Advanced Computer Science Universiteit LeidenRA LeidenThe Netherlands

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