• DocumentCode
    3521509
  • Title

    Research on Mining Frequent Itemsets Based on Bitwise AND Algorithm

  • Author

    Guo Xiaoli ; Feng Li ; Guo Ping

  • Author_Institution
    Sch. of Inf. Eng., Northeast Dianli Univ., Jilin, China
  • fYear
    2011
  • fDate
    28-29 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    According to the characteristics of the data flow, the article puts forward a new frequent itemsets mining algorithm based on bitwise and computation. Algorithm uses basic window for unit, and update sliding window in memory using arrays structure maintenance item of frequent information, finally by the frequent items between the bitwise and operations to get all the frequent itemsets. Algorithm in each basic window goes into the sliding window after dynamically update arrays, analysis and experiment shows that the algorithm has better performance.
  • Keywords
    data flow computing; data mining; user interfaces; array structure maintenance; bitwise AND algorithm; data flow characteristics; frequent itemset mining; memory sliding window; Algorithm design and analysis; Arrays; Data mining; Heuristic algorithms; Itemsets; Memory management; Substations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9855-0
  • Electronic_ISBN
    978-1-4244-9857-4
  • Type

    conf

  • DOI
    10.1109/ISA.2011.5873398
  • Filename
    5873398