• DocumentCode
    3382877
  • Title

    Query fuzzy association rules in relational database

  • Author

    Shu, Joyce Y. ; Tsang, Eric C C ; Yeung, Daniel S.

  • Author_Institution
    Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
  • fYear
    2001
  • fDate
    25-28 July 2001
  • Firstpage
    2989
  • Abstract
    An important issue to extend database management systems functionality is to allow the expression of imprecise queries to make these systems able to satisfy user needs more closely. In the last few years, some authors have dealt with the problem of relaxing the relational model in order to admit some imprecision. Two significant data mining problems have been addressed recently, namely, mining fuzzy association. rules, and set-oriented mining for association rules in relational database (SETM algorithms). At present, the problem of how to express the mining fuzzy association rules algorithm as SQL queries has not been proposed. In this paper, we attempt to develop a fuzzy version of SETM algorithms that can be expressed as SQL queries in relational databases and discuss optimization of the algorithm
  • Keywords
    SQL; data mining; fuzzy set theory; relational databases; SETM algorithms; SQL queries; association rules; data mining; fuzzy association rules; relational database; relational model; set-oriented mining; Association rules; Banking; Data mining; Database languages; Database systems; Fuzzy sets; Graphical user interfaces; Industrial relations; Mining industry; Relational databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-7078-3
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2001.943703
  • Filename
    943703