• DocumentCode
    3026863
  • Title

    An improved prefixspan algorithm research for sequential pattern mining

  • Author

    Liu Pei-yu ; Gong Wei ; Jia Xian

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Ji´nan, China
  • Volume
    1
  • fYear
    2011
  • fDate
    9-11 Dec. 2011
  • Firstpage
    103
  • Lastpage
    108
  • Abstract
    PrefixSpan, the classic sequential patterns mining algorithm, has the problem of large expenses in constructing projected databases. A Sequential Patterns Mining based on Improved PrefixSpan (SPMIP) algorithm is proposed on the basic of the defects above. This algorithm can reduce the scale of projected databases and the time of scanning projected databases through adding the pruning step and reducing the scanning of certain specific sequential patterns production. In this way, algorithm efficiency can be raised, and the sequential patterns needed are obtained. The experiment results show that the SPMIP algorithm is more efficient than the PrefixSpan algorithm while the sequential patterns obtained are not affected.
  • Keywords
    data mining; database management systems; pattern clustering; sequences; SPMIP algorithm; improved PrefixSpan algorithm; projected database; pruning step; sequential pattern mining; Algorithm design and analysis; Concrete; Data mining; Databases; Heuristic algorithms; Production; Software algorithms; PrefixSpan; Project database; Pruning; Scanning; Squential patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IT in Medicine and Education (ITME), 2011 International Symposium on
  • Conference_Location
    Cuangzhou
  • Print_ISBN
    978-1-61284-701-6
  • Type

    conf

  • DOI
    10.1109/ITiME.2011.6130794
  • Filename
    6130794