• DocumentCode
    468353
  • Title

    A Two-Way Hybrid Algorithm for Maximal Frequent Itemsets Mining

  • Author

    Chen, Fu-zan ; Li, Min-qiang

  • Author_Institution
    Tianjin Univ., Tianjin
  • Volume
    3
  • fYear
    2007
  • fDate
    24-27 Aug. 2007
  • Firstpage
    499
  • Lastpage
    503
  • Abstract
    A new two-way-hybrid algorithm for mining maximal frequent itemsets is proposed. A flexible two-way-hybrid search method is given. The two-way-hybrid search begins the mining procedure in both the top-down and bottom-up directions at the same time. Moreover, information gathered in the bottom-up can be used to prune the search space in the other top-down direction. Some efficient decomposition and pruning strategies are implied in this method, which can reduce the original search space rapidly in the iterations. Experimental and analytical results are presented in the end.
  • Keywords
    data mining; set theory; tree data structures; tree searching; bottom-up search; maximal frequent itemset mining; pruning strategy; top-down search; tree data structure; Data mining; Frequency shift keying; Fuzzy systems; Itemsets; Optimization methods; Search methods; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2874-8
  • Type

    conf

  • DOI
    10.1109/FSKD.2007.130
  • Filename
    4406288