• DocumentCode
    3182502
  • Title

    Mining complete fuzzy frequent itemsets by tree structures

  • Author

    Hong, Tzung-Pei ; Lin, Tsung-Ching ; Tsung-Ching Lin

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    10-13 Oct. 2010
  • Firstpage
    563
  • Lastpage
    567
  • Abstract
    In this paper, we attempt to extend the fuzzy FP-tree mining process to mine all fuzzy frequent itemsets, instead of only the representative linguistic terms, from a set of quantitative transactions. A multiple fuzzy-term FP (MFFP) tree with the consideration of fuzzy operations is proposed to help the execution of the fuzzy mining process. The corresponding MFFP-growth mining algorithm is also designed to derive all fuzzy frequent itemsets from the tree structure by fuzzy operations. Experimental results also show the performance of the proposed approach.
  • Keywords
    data mining; fuzzy set theory; tree data structures; fuzzy frequent itemsets mining; multiple fuzzy term FP tree mining process; tree structure; Association rules; Itemsets; fuzzy data mining; fuzzy frequent itemset; fuzzy region; fuzzy set; quantitative value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-6586-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.2010.5642016
  • Filename
    5642016