• DocumentCode
    1574088
  • Title

    An efficient projected database method for mining sequential association rules

  • Author

    Chen, Yi-Chun ; Lee, Guanling

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Dong Hwa Univ., Hualien, Taiwan
  • fYear
    2010
  • Firstpage
    274
  • Lastpage
    278
  • Abstract
    The mining of sequential patterns has been studied for several years, however, to our best knowledge, no study has considered the mining of sequential association rules despite such rules also providing valuable knowledge about many real applications. The sequential association rule represent that a set of items usually occur after a specific order sequence. In this paper, the concept of sequential association rule is proposed and an efficient algorithm, the SAR (Sequential Association Rules) algorithm, is proposed to discover these hidden knowledge. A set of experiments is also performed to show that the benefit of our approach.
  • Keywords
    data mining; SAR algorithm; projected database method; sequential association rules mining; sequential pattern mining; Algorithm design and analysis; Association rules; Itemsets; Obesity; data mining; projected database method; sequential association rule;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Information Management (ICDIM), 2010 Fifth International Conference on
  • Conference_Location
    Thunder Bay, ON
  • Print_ISBN
    978-1-4244-7572-8
  • Type

    conf

  • DOI
    10.1109/ICDIM.2010.5664724
  • Filename
    5664724