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Extraction of Coverings as Monotone DNF Formulas

  • Kouichi Hirata
  • Ryosuke Nagazumi
  • Masateru Harao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2843)

Abstract

In this paper, we extend monotone monomials as large itemsets in association rule mining to monotone DNF formulas. First, we introduce not only the minimum support but also the maximum overlap, which is a new measure how much all pairs of two monomials in a monotone DNF formula commonly cover data. Next, we design the algorithm dnf_cover to extract coverings as monotone DNF formulas satisfying both the minimum support and the maximum overlap. In the algorithm dnf_cover, first we collect the monomials of which support value is not only more than the minimum support but also less than the minimum support as seeds. Secondly we construct the coverings as monotone DNF formulas, by combining monomials in seeds under the minimum support and the maximum overlap. Finally, we apply the algorithm dnf_cover to bacterial culture data.

Keywords

Association Rule Minimum Support Association Rule Mining Transaction Database Large Itemsets 
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 2003

Authors and Affiliations

  • Kouichi Hirata
    • 1
  • Ryosuke Nagazumi
    • 2
  • Masateru Harao
    • 1
  1. 1.Department of Artificial Intelligence 
  2. 2.Graduate School of Computer Science and Systems EngineeringKyushu Institute of TechnologyIizukaJapan

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