• DocumentCode
    693232
  • Title

    Mining fuzzy frequent itemsets by projection techniques

  • Author

    Guo-Cheng Lan ; Tzung-Pei Hong ; Yi-Hsin Lin ; Chun-Wei Tsai

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • Volume
    04
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    1691
  • Lastpage
    1694
  • Abstract
    Different from the existing algorithms, this work presents an efficient projection-based algorithm to find fuzzy frequent itemsets in quantitative databases. In particular, the proposed algorithm adopts the two strategies, indexing and pruning, to effectively speed up the execution efficiency in mining. In the experimental evaluation, the results on a synthetic dataset show the proposed algorithm executes faster than our previous algorithm.
  • Keywords
    data mining; fuzzy set theory; indexing; fuzzy frequent itemset mining; indexing strategy; projection techniques; projection-based algorithm; pruning strategy; quantitative databases; synthetic dataset; Abstracts; Itemsets; Data mining; fuzzy data mining; fuzzy frequent itemsets; indexing strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890870
  • Filename
    6890870
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=693232