• DocumentCode
    2848700
  • Title

    Research on Positive and Negative Association Rules Based on "Interest-Support-Confidence" Framework

  • Author

    Shen, Yanguang ; Liu, Jie ; Yang, Zhiyong

  • Author_Institution
    Sch. of Inf. & Electron. Eng., Hebei Univ. of Eng., Handan, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The traditional method based on "support-confidence" framework could bring a large number of irrelevant or even misleading association rules. In view of the problem of evaluation standards of association rules, we increase interest measure in the evaluation standards, and give the definition of interest measure and positive and negative association rules method based on "interest-support-confidence" framework, which can be used to mine negative association rules. We applied this method in data mining of e-business , and through comparing with the Apriori method, this method can effectively reduce the amount of positive association rules, and produce more meaningful negative association rules.
  • Keywords
    data mining; electronic commerce; apriori method; data mining; e-business; evaluation standards; interest-support-confidence framework; negative association rule; positive association rule; Area measurement; Association rules; Boring; Data mining; Decision making; Investments; Marketing and sales; Measurement standards; Printers; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5365239
  • Filename
    5365239