• DocumentCode
    3106111
  • Title

    bitSPADE: A Lattice-based Sequential Pattern Mining Algorithm Using Bitmap Representation

  • Author

    Aseervatham, Sujeevan ; Osmani, Aomar ; Viennet, Emmanuel

  • Author_Institution
    Inst. Galilee, Univ. Paris 13, Villetaneuse
  • fYear
    2006
  • fDate
    18-22 Dec. 2006
  • Firstpage
    792
  • Lastpage
    797
  • Abstract
    Sequential pattern mining allows to discover temporal relationship between items within a database. The patterns can then be used to generate association rules. When the databases are very large, the execution speed and the memory usage of the mining algorithm become critical parameters. Previous research has focused on either one of the two parameters. In this paper, we present bitSPADE, a novel algorithm that combines the best features of SPAM, one of the fastest algorithm, and SPADE, one of the most memory efficient algorithm. Moreover, we introduce a new pruning strategy that enables bitSPADE to reach high performances. Experimental evaluations showed that bitSPADE ensures an efficient tradeoff between speed and memory usage by outperforming SPADE by both speed and memory usage factors more than 3.4 and SPAM by a memory consumption factor up to more than an order of magnitude.
  • Keywords
    data mining; association rules; bitSPADE; bitmap representation; lattice-based sequential pattern mining algorithm; memory consumption factor; memory usage; pruning strategy; temporal relationship; very large databases; Association rules; Customer satisfaction; DVD; Data mining; Frequency; Genetics; Lattices; Spatial databases; TV; Unsolicited electronic mail;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2006. ICDM '06. Sixth International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1550-4786
  • Print_ISBN
    0-7695-2701-7
  • Type

    conf

  • DOI
    10.1109/ICDM.2006.28
  • Filename
    4053104