• DocumentCode
    501370
  • Title

    Sequence Alignment Algorithm in Similarity Measurement

  • Author

    Le, Li ; Hongchang, Chen ; Lixiong, Liu

  • Author_Institution
    Nat. Digital Switching Syst. Eng. & Technol. R&D Center, Zhengzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    15-17 May 2009
  • Firstpage
    453
  • Lastpage
    456
  • Abstract
    The first and foremost question needed to be considered in clustering analysis is how to measure the similarity that decides the result of clustering immediately. However, are many shortcomings in traditional methods. This paper deals with similarity of English texts using sequence alignment which is always used in biology informatics. This method do not use traditional way that transform texts so that it is more intuitive. It can improve the rate and the result of clustering preferably. The test demonstrates the new approach is reasonable and efficient.
  • Keywords
    pattern clustering; text analysis; English texts; biology informatics; clustering analysis; sequence alignment; similarity measurement; Algorithm design and analysis; Clustering algorithms; Covariance matrix; Information analysis; Information technology; Partitioning algorithms; Research and development; Sequences; Switching systems; Systems engineering and theory; clustering; sequence alignment; similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications, 2009. IFITA '09. International Forum on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-0-7695-3600-2
  • Type

    conf

  • DOI
    10.1109/IFITA.2009.119
  • Filename
    5231658