• DocumentCode
    2542740
  • Title

    A fuzzy weight algorithm for mining infrequent association rules

  • Author

    Zhengxin, Li ; Fengming, Zhang ; Xiaodong, Lin ; Kewu, Li

  • Author_Institution
    Eng. Inst., Air Force Eng. Univ. AFEU, Xi´´an, China
  • fYear
    2010
  • fDate
    16-18 April 2010
  • Firstpage
    94
  • Lastpage
    97
  • Abstract
    The paper introduces the conception of significance and presents a new algorithm -a fuzzy weight algorithm with multiple supports for mining association rules, which is based on fuzzy-comprehensive evaluation and the algorithm of multiple minimum supports. The new algorithm takes support and significance into consideration at the same time when large itemsets are produced, making the filter criterion more reasonable and not missing items with high significance but low supports.
  • Keywords
    data mining; fuzzy set theory; data mining; filter criterion; fuzzy weight algorithm; mining association rules; Association rules; Data mining; Electronic mail; Filters; Itemsets; Transaction databases; association rules; data mining; fuzzy-comprehensive evaluation; weight algorithm with multiple supports;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5263-7
  • Electronic_ISBN
    978-1-4244-5265-1
  • Type

    conf

  • DOI
    10.1109/ICIME.2010.5477565
  • Filename
    5477565