• DocumentCode
    3307259
  • Title

    The research of improved association rules mining Apriori algorithm

  • Author

    Huiying Wang ; Xiangwei Liu

  • Author_Institution
    Sch. of Public Adm., Univ. of Int. Bus. & Econ., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    961
  • Lastpage
    964
  • Abstract
    This paper points out the bottleneck of classical Apriori´s algorithm, presents an improved association rule mining algorithm. The new algorithm is based on reducing the times of scanning candidate sets and using hash tree to store candidate itemsets. According to the running result of the algorithm, the processing time of mining is decreased and the efficiency of algorithm has improved.
  • Keywords
    data mining; candidate itemsets; classical a priori algorithm; hash tree; improved association rule mining algorithm; Algorithm design and analysis; Association rules; Economics; Educational institutions; Itemsets; Apriori algorithm; Data mining; association rule; frequent itemset;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-61284-180-9
  • Type

    conf

  • DOI
    10.1109/FSKD.2011.6019685
  • Filename
    6019685
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3307259