Computing

, 93:1 | Cite as

Query-based association rule mining supporting user perspective

  • Seung-Jae Song
  • Eung-Hee Kim
  • Hong-Gee Kim
  • Harshit Kumar
Article

Abstract

Two parameters, namely support and confidence, in association rule mining, are used to arrange association rules in either increasing or decreasing order. These two parameters are assigned values by counting the number of transactions satisfying the rule without considering user perspective. Hence, an association rule, with low values of support and confidence, but meaningful to the user, does not receive the same importance as is perceived by the user. Reflecting user perspective is of paramount importance in light of improving user satisfaction for a given recommendation system. In this paper, we propose a model and an algorithm to extract association rules, meaningful to a user, with an ad-hoc support and confidence by allowing the user to specify the importance of each transaction. In addition, we apply the characteristics of a concept lattice, a core data structure of Formal Concept Analysis (FCA) to reflect subsumption relation of association rules when assigning the priority to each rule. Finally, we describe experiment results to verify the potential and efficiency of the proposed method.

Keywords

Data mining Association rule Formal concept analysis User perspective 

Mathematics Subject Classification (2000)

68R01 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Seung-Jae Song
    • 1
  • Eung-Hee Kim
    • 1
  • Hong-Gee Kim
    • 1
  • Harshit Kumar
    • 1
    • 2
  1. 1.Biomedical Knowledge Engineering Lab, Dental Research InstituteSeoul National UniversitySeoulKorea
  2. 2.Department of Computer ScienceUniversity of SuwonHwaseongKorea

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