• DocumentCode
    1925698
  • Title

    An Efficient Frequent Itemset Mining Algorithm

  • Author

    Luo, Ke ; Zhang, Xue-mao

  • Author_Institution
    Changsha Univ. of Sci. & Technol., Changsha
  • Volume
    2
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    756
  • Lastpage
    761
  • Abstract
    Frequent itemset mining is a critical step in association rule mining and plays an important role in many data mining tasks including strong rules, correlations and sequential rules. Diffset is an efficient frequent itemset mining algorithm which uses vertical database layout. An efficient hybrid algorithm DiffsetHybrid is brought out. The tests indicate that the new algorithm shows good performance with both sparse datasets and dense datasets.
  • Keywords
    data mining; database management systems; Diffset frequent itemset mining algorithm; DiffsetHybrid algorithm; association rule mining; data mining tasks; sequential rules; strong rules; vertical database layout; Association rules; Cybernetics; Data mining; Electronic mail; Itemsets; Machine learning; Machine learning algorithms; Telecommunications; Testing; Transaction databases; Diffset; DiffsetHybrid; Frequent itemset mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370245
  • Filename
    4370245
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1925698