• DocumentCode
    2004430
  • Title

    X-μ fuzzy association rule method

  • Author

    Lewis, David ; Martin, Trevor P.

  • Author_Institution
    Dept. of Eng. Math., Univ. of Bristol, Bristol, UK
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    144
  • Lastpage
    150
  • Abstract
    Association rule mining theory, and practice, requires the ability to calculate the cardinalities of subsets. In association rule mining on fuzzy sets, this is also the case. However, there are multiple options for calculating cardinalities due to the nature of fuzzy sets. In this paper we introduce the “X-μ Fuzzy Association Rule method” of calculation, a methodology for use within fuzzy association rule mining. This method uses the X-μ representation of fuzzy sets and its respective cardinality calculation, which retains the fuzzy nature of fuzzy set cardinality through the full process of association rule processing.
  • Keywords
    data mining; fuzzy set theory; X-μ fuzzy association rule method; X-μ representation; association rule mining theory; association rule processing; fuzzy association rule mining; fuzzy set cardinality; fuzzy sets; Association rules; Customer satisfaction; Databases; Fuzzy set theory; Fuzzy sets; Hair; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2013 13th UK Workshop on
  • Conference_Location
    Guildford
  • Print_ISBN
    978-1-4799-1566-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2013.6651299
  • Filename
    6651299