• DocumentCode
    3067257
  • Title

    A Decomposition Approach for Mining Frequent Itemsets

  • Author

    Huang, Jen-Peng ; Lan, Guo-Cheng ; Kuo, Huang-Cheng ; Hong, Tzung-Pei

  • Author_Institution
    Southern Taiwan Univ. of Technol., Tainan
  • Volume
    2
  • fYear
    2007
  • fDate
    26-28 Nov. 2007
  • Firstpage
    605
  • Lastpage
    608
  • Abstract
    In this paper, instead of proposing the fastest mining algorithm in the world, we present a new approach in mining association rules. We propose a new algorithm - GRA (Gradational Reduction Approach). It adopts three mechanisms to increase the performance of mining. First, GRA algorithm uses a hash based technique, Hash MAP, which is similar to Hash Table to increase the access efficiency. Second, GRA algorithm uses an infrequent itemsets filtering mechanism to avoid generating a great deal of infrequent sub-itemsets of transaction records. Third, in order to reduce the size of database, GRA algorithm uses gradational reduction mechanism which uses the frequent itemsets as the information of filtration mechanisms to erase the infrequent items from database at every phase. GRA algorithm can decrease a large number of non-frequent itemsets and increase the utility rate of memory.
  • Keywords
    data mining; association rules mining; decomposition approach; fast mining algorithm; frequent itemsets mining; gradational reduction approach; Association rules; Computer science; Data mining; Electronic mail; Filtering algorithms; Filtration; Information analysis; Information management; Itemsets; Transaction databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-0-7695-2994-1
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2007.11
  • Filename
    4457782