• DocumentCode
    2420347
  • Title

    Efficiently Mining Maximal Frequent Itemsets Based on Digraph

  • Author

    Ren, Zhibo ; Zhang, Qiang ; Ma, Xiujuan

  • Author_Institution
    Hebei Univ., Baoding
  • Volume
    2
  • fYear
    2007
  • fDate
    24-27 Aug. 2007
  • Firstpage
    140
  • Lastpage
    143
  • Abstract
    We present MFIMiner, a new algorithm for mining maximal frequent itemsets. The algorithm has a preprocessing phase in which a digraph is constructed. The digraph represents the set of the frequent 2-itemsets which is the key issue of the performance of the data mining. Then the search for maximal frequent itemsets is done in the digraph. Experiments show that the algorithm is efficient not only to dense data, but to sparse data.
  • Keywords
    data mining; MFIMiner; data mining; digraph; maximal frequent itemset mining; Data mining; Energy management; Frequency; Itemsets; Power generation economics; Tail; Technology management; 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.2007.268
  • Filename
    4406061
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2420347