• DocumentCode
    3228454
  • Title

    Fast and efficient mining for frequent patterns on biological sequence

  • Author

    Wei, Liu ; Ling, Chen

  • Author_Institution
    Sch. of Inf. Technol., Nanjing Xiaozhuang Univ., Nanjing, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    971
  • Lastpage
    975
  • Abstract
    Biological sequential frequent pattern mining is one of the important research fields in biological sequential data mining. In order to overcome the shortcomings of traditional algorithms, we proposed a fast algorithm SSPM here. We used longer patterns and prefix tree of primary frequent patterns for mining which avoided plenty of irrelevant patterns. The experimental results show that our algorithm could not only improve the performance but also achieve effective mining results.
  • Keywords
    bioinformatics; data mining; biological sequence; biological sequential data mining; pattern mining; prefix tree; Algorithm design and analysis; Computers; Proteins; biological sequence; frequent pattern mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645133
  • Filename
    5645133