• DocumentCode
    493695
  • Title

    Mining Valid Association Rules in Incomplete Information Systems

  • Author

    Wang, Lili ; Yang, Guangjun

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Dezhou Univ., Dezhou
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 March 2009
  • Firstpage
    633
  • Lastpage
    636
  • Abstract
    Extracting the association rules is an important research topic among the various data mining problems. Based on the rough set theory which is a powerful tool in dealing with incompleteness and uncertainty, an algorithm to mine association rules in incomplete information systems is presented. In the new algorithm, the support and confidence are redefined and a new judgment criterion is introduced in. The algorithm can mine the positive, invalid and negative association rules directly without processing missing values. The experiment shows that the new algorithm has short execution times, and can mine effective association rules efficiently.
  • Keywords
    data mining; information systems; incomplete information systems; judgment criterion; mining valid association rules; Association rules; Computer science; Computer science education; Data engineering; Data mining; Decision making; Educational technology; Information systems; Set theory; Uncertainty; association mining; expectation effect; incomplete information systems; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-1-4244-3581-4
  • Type

    conf

  • DOI
    10.1109/ETCS.2009.402
  • Filename
    4959117