• DocumentCode
    1875050
  • Title

    A General Framework for Fuzzy Data Mining

  • Author

    Zhao, Jitao ; Yao, Lin

  • Author_Institution
    Dept. of Educ. Technol. & Inf., Xuchang Univ., Xuchang, China
  • fYear
    2010
  • fDate
    10-12 Dec. 2010
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Mining association rules is one of the most important tasks in data mining. Several approaches generalizing association rules to fuzzy association rules have been proposed. In this paper we present a general framework for mining fuzzy association rule. Based on apriori algorithm, a new algorithm for mining fuzzy association rules is proposed. Experimental results illustrate the algorithm is more effective.
  • Keywords
    data mining; fuzzy set theory; relational databases; apriori algorithm; association rules; fuzzy association rules; fuzzy data mining; Association rules; Diseases; Helium; Itemsets; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5391-7
  • Electronic_ISBN
    978-1-4244-5392-4
  • Type

    conf

  • DOI
    10.1109/CISE.2010.5676960
  • Filename
    5676960
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1875050