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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106402

    Title: Fuzzy association rule mining with type-2 membership functions
    Authors: Chen, C. H.;Li, Y.;Hong, T. P.
    Keywords: Data mining;Fuzzy association rule;Membership functions;Type-2 fuzzy set
    Date: 2015-03-23
    Issue Date: 2016-04-27 11:11:57 (UTC+8)
    Publisher: Springer International Publishing
    Abstract: In this paper, a fuzzy association rule mining approach with type-2
    membership functions is proposed for dealing with data uncertainty. It first
    transfers quantitative values in transactions into type-2 fuzzy values. Then, according
    to a predefined split number of points, they are reduced to type-1 fuzzy
    values. At last, the fuzzy association rules are derived by using these fuzzy values.
    Experiments on a simulated dataset were made to show the effectiveness of
    the proposed approach.
    Relation: Intelligent Information and Database Systems Part II LNAI 9012, pp.128-134
    DOI: 10.1007/978-3-319-15705-4_13
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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