• DocumentCode
    441779
  • Title

    Novel measurement for mining effective association rules

  • Author

    Wei, Jin-Mao ; Yi, Wei-Guo ; Wang, Ming-Yang

  • Author_Institution
    Inst. of Computational Intelligence, Northeast Normal Univ., ChangChun, China
  • Volume
    3
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    1660
  • Abstract
    In this paper, we analyze the method of support-confidence framework when mining association rules. In order to avoid the limitation in the criterion, we propose a new method of match as the substitution of confidence. We analyze in detail the property of the proposed measurement. Experimental results show that there is higher correlation between the antecedent and the consequent of the rules produced by the improved method compared with the rules produced by the support-confidence framework. Furthermore, the improved method decreases the generation of redundancy rules.
  • Keywords
    data mining; association rules; data mining; support-confidence framework; Association rules; Computational intelligence; Data mining; Electronic mail; Frequency; Knowledge engineering; Laboratories; Merchandise; Neural networks; Transaction databases; Data mining; association rules; correlation; match;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527211
  • Filename
    1527211