• DocumentCode
    536233
  • Title

    Research of an association rule mining algorithm based on FP tree

  • Author

    Juan, Li ; De-ting, Ming

  • Author_Institution
    Comput. & Inf. Eng. Inst., Jiangxi Agric. Univ., Nanchang, China
  • Volume
    1
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    559
  • Lastpage
    563
  • Abstract
    Based on analyzing an association rule mining algorithm called FP tree, a new association rule mining algorithm called QFP was presented. Through scanning the database only once, the QFP algorithm can convert a transaction database into a QFP tree after data preprocessing, and then do the association rule mining of the tree. The QFP algorithm is more integrity than the FP_growth algorithm, and retain the complete information for mining frequent patterns; it will not destroy the long pattern of any transaction, and significantly reduce the non-relevant information. Experiments show that the QFP algorithm is more efficient if the aspect of time than the FP_growth algorithm.
  • Keywords
    data mining; transaction processing; tree searching; FP tree; QFP algorithm; association rule mining; data preprocessing; frequent pattern; transaction database; Databases; Electronics packaging; Random access memory; Association rule mining; FP_growth algorithm; Frequent Pattern(FP); QFP algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658443
  • Filename
    5658443