• DocumentCode
    3166273
  • Title

    Prism: A Primal-Encoding Approach for Frequent Sequence Mining

  • Author

    Gouda, Karam ; Hassaan, Mosab ; Zaki, Mohammed J.

  • Author_Institution
    Fac. of Sci., Benha
  • fYear
    2007
  • fDate
    28-31 Oct. 2007
  • Firstpage
    487
  • Lastpage
    492
  • Abstract
    Sequence mining is one of the fundamental data mining tasks. In this paper we present a novel approach called Prism, for mining frequent sequences. Prism utilizes a vertical approach for enumeration and support counting, based on the novel notion o/prime block encoding, which in turn is based on prime factorization theory. Via an extensive evaluation on both synthetic and real datasets, we show that Prism outperforms popular sequence mining methods like SPADE [10], PrefixSpan [6] and SPAM [2], by an order of magnitude or more.
  • Keywords
    block codes; data mining; data mining; frequent sequence mining; prime block encoding; prime factorization theory; Bioinformatics; Computer science; Data mining; Databases; Economic indicators; Encoding; Itemsets; Mathematics; USA Councils; Unsolicited electronic mail;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
  • Conference_Location
    Omaha, NE
  • ISSN
    1550-4786
  • Print_ISBN
    978-0-7695-3018-5
  • Type

    conf

  • DOI
    10.1109/ICDM.2007.33
  • Filename
    4470278