• DocumentCode
    3255427
  • Title

    An algorithm for reusable uninteresting rules in association rule mining

  • Author

    Thongtae, Pongsiam ; Srisuk, Sanun

  • Author_Institution
    Dept. of Comput. Eng., Mahanakorn Univ. of Technol., Bangkok
  • fYear
    2008
  • fDate
    4-6 Aug. 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we present a new framework for reusable association rule mining based on chi2 and odds ratio. We start at mining the association rules using standard Apriori algorithm. The strong rules are defined as association rules, while the weak rules will be evaluated by our proposed method. Firstly, the weak rules must be converted to 2 times 2 contingency table. We then compute the relationship between variables using chi2 and odds ratio. If the weak rules are related to each other with positive or negative relationship, then the weak rules will also be determined as association rules. Our system is evaluated with experiments on the crime data.
  • Keywords
    data mining; contingency table; reusable association rule mining; reusable uninteresting rules; standard apriori algorithm; weak rules; Association rules; Data mining; Itemsets; Pattern analysis; Testing; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Digital Information and Web Technologies, 2008. ICADIWT 2008. First International Conference on the
  • Conference_Location
    Ostrava
  • Print_ISBN
    978-1-4244-2623-2
  • Electronic_ISBN
    978-1-4244-2624-9
  • Type

    conf

  • DOI
    10.1109/ICADIWT.2008.4664326
  • Filename
    4664326