• DocumentCode
    568151
  • Title

    An improved association rule algorithm based on Itemset Matrix and Cluster Matrix

  • Author

    Jian, Peng ; Xiao-ling, Wang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Hunan Inst. of Humanities, Loudi, China
  • fYear
    2012
  • fDate
    14-17 July 2012
  • Firstpage
    834
  • Lastpage
    837
  • Abstract
    Through the analysis of the method of association rules, an improved algorithm in association rules based on Itemset Matrix(ISM) and Cluster Matrix(CMa) is put forward. The algorithm can get the new frequent itemsets just through scanning the updated data once again, when the database and the minimum support degree are changed. Studies and analysis of the algorithm show that it just need to scan the database once, so it has the virtues in high-speed producing frequent k-itemsets and less time cost. And it improves the efficiency of the association mining, can fulfill the request of shortening the time of mining.
  • Keywords
    data mining; matrix algebra; pattern clustering; CMa; ISM; association mining efficiency improvement; cluster matrix; frequent k-itemsets mining; improved association rule algorithm; itemset matrix; Algorithm design and analysis; Association rules; Clustering algorithms; Itemsets; Vectors; Cluster Matrixes(CMa); Itemset Matrixes(ISM); association rules; association vector;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2012 7th International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-0241-8
  • Type

    conf

  • DOI
    10.1109/ICCSE.2012.6295199
  • Filename
    6295199