• DocumentCode
    2308141
  • Title

    A two-phase fuzzy mining approach

  • Author

    Lin, Chun-Wei ; Hong, Tzung-Pei ; Lu, Wen-Hsiang

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, we propose a two-phase fuzzy mining approach based on a tree structure to discover fuzzy frequent itemsets from a quantitative database. A simple tree structure called the upper-bound fuzzy frequent-pattern tree (abbreviated as UBFFP tree) is designed to help achieve the purpose. The two-phase fuzzy mining approach can easily derive the upper-bound fuzzy supports of itemsets through the tree and prune unpromising itemsets in the first phase, and then finds the actual frequent fuzzy itemsets in the second phase. Experimental results also show the good performance of the proposed approach.
  • Keywords
    data mining; fuzzy set theory; tree data structures; UBFFP tree; fuzzy frequent itemset; quantitative database; tree structure; two-phase fuzzy mining; upper-bound fuzzy frequent-pattern tree; Algorithm design and analysis; Association rules; Computer science; Construction industry; Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-6919-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2010.5584373
  • Filename
    5584373