• DocumentCode
    476742
  • Title

    A new method for mining maximal frequent itemsets

  • Author

    Nadimi-Shahraki, Mohammad ; Mustapha, Norwati ; Sulaiman, Md Nasir B. ; Mamat, Ali B.

  • Author_Institution
    Faculty of Computer Science and Information Technology, University of Putra Malaysia, 43400, Selangor, Malaysia
  • Volume
    2
  • fYear
    2008
  • fDate
    26-28 Aug. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we propose a new method for mining maximal frequent itemsets. Our method introduces an efficient database encoding technique, a novel tree structure called PC_Tree and also PC_Miner algorithm. The database encoding technique utilizes Prime number characteristics and transforms each transaction into a positive integer that has all properties of its items. The PC_Tree is a simple tree structure but yet powerful to capture whole of transactions by one database scan. The PC_Miner algorithm traverses the PC_Tree and builds the gcd (greatest common divisor) set of its nodes to mine maximal frequent itemsets. Experiments verify the efficiency and advantages of the proposed method.
  • Keywords
    Computer science; Data mining; Encoding; Information technology; Itemsets; Search methods; Transaction databases; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology, 2008. ITSim 2008. International Symposium on
  • Conference_Location
    Kuala Lumpur, Malaysia
  • Print_ISBN
    978-1-4244-2327-9
  • Electronic_ISBN
    978-1-4244-2328-6
  • Type

    conf

  • DOI
    10.1109/ITSIM.2008.4631691
  • Filename
    4631691