• DocumentCode
    2990478
  • Title

    Based on Frequent Itemset for Maximal Frequent Itesets

  • Author

    Chen, Donghui ; Liu, Zhijing

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    3416
  • Lastpage
    3418
  • Abstract
    This paper proposes a maximal frequent itemsets mining algorithm BFI-MFI (Based on Frequent Itemset for maximal frequent itemsets). A maximal frequent itemset in frequent itemsets can be confirmed through detecting whether exiting their superset. This algorithm provides a new method, which improve the mining efficiency.
  • Keywords
    data mining; BFI-MFI algorithm; association rule; data mining; maximal frequent itemset; mining algorithm; superset; Algorithm design and analysis; Computers; Data mining; Educational institutions; Itemsets; Research and development; Software algorithms; association rule; data mining; frequent itemset; maximal frequent itemset;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.1424
  • Filename
    5630402