Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets

  • Yves Bastide
  • Nicolas Pasquier
  • Rafik Taouil
  • Gerd Stumme
  • Lotfi Lakhal
Conference paper

DOI: 10.1007/3-540-44957-4_65

Volume 1861 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Bastide Y., Pasquier N., Taouil R., Stumme G., Lakhal L. (2000) Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets. In: Lloyd J. et al. (eds) Computational Logic — CL 2000. Lecture Notes in Computer Science, vol 1861. Springer, Berlin, Heidelberg

Abstract

The problem of the relevance and the usefulness of extracted association rules is of primary importance because, in the majority of cases, real-life databases lead to several thousands association rules with high confidence and among which are many redundancies. Using the closure of the Galois connection, we define two new bases for association rules which union is a generating set for all valid association rules with support and confidence. These bases are characterized using frequent closed itemsets and their generators; they consist of the non-redundant exact and approximate association rules having minimal antecedents and maximal consequents, i.e. the most relevant association rules. Algorithms for extracting these bases are presented and results of experiments carried out on real-life databases show that the proposed bases are useful, and that their generation is not time consuming.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Yves Bastide
    • 1
  • Nicolas Pasquier
    • 1
  • Rafik Taouil
    • 1
  • Gerd Stumme
    • 1
    • 2
  • Lotfi Lakhal
    • 1
  1. 1.L.I.M.O.S.Université Blaise Pascal - Clermont-Ferrand IIAubière cedexFrance
  2. 2.Fachbereich MathematikTechnische Universität DarmstadtDarmstadtGermany