• DocumentCode
    694732
  • Title

    An Improved Association Rules Mining Algorithm Based on Power Set and Hadoop

  • Author

    Weijun Mao ; Weibin Guo

  • Author_Institution
    Dept. of Comput. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2013
  • fDate
    7-8 Dec. 2013
  • Firstpage
    236
  • Lastpage
    241
  • Abstract
    The association rules mining has an very important impact in data mining. As the rapid growth of datasets, the required memory increase seriously and the operating efficiency declines rapidly. Cloud computing provides efficient and cheap solutions to analyze and implement the association rules mining algorithms in parallel. This paper proposes an improved association mining algorithm based on power set and MapReduce programming model, which can process massive datasets with a cluster of machines on Hadoop platform. The results of the numerical experiments show that the proposed algorithm can achieve higher efficiency in the association rules mining.
  • Keywords
    cloud computing; data mining; parallel programming; Hadoop; MapReduce programming model; association rules mining algorithm; cloud computing; data mining; operating efficiency; parallel programming; power set; Algorithm design and analysis; Association rules; Cloud computing; Clustering algorithms; Itemsets; Association rules mining; Cloud computing; Data mining; MapReduce; Power set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
  • Conference_Location
    Guangzhou
  • Type

    conf

  • DOI
    10.1109/ISCC-C.2013.39
  • Filename
    6973598