• DocumentCode
    3473796
  • Title

    An Improved K-Means Text Clustering Algorithm Based on Local Search

  • Author

    Liu, Xiangwei

  • Author_Institution
    Dept. of MIS, Tianjin Univ. of Finance & Econ., Tianjin
  • fYear
    2008
  • fDate
    12-14 Oct. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a new text clustering algorithm based on local search and K-means (LSKM) and explains the characteristic of this algorithm theoretically. The experimental results of three standard test collections show that the new algorithm is better than K-means and the theoretical analysis is also testified in this paper.
  • Keywords
    learning (artificial intelligence); pattern clustering; search problems; text analysis; K-means text clustering algorithm; combinatorial optimization problem; local search; unsupervised learning; Algorithm design and analysis; Clustering algorithms; Finance; Partitioning algorithms; Testing; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-2107-7
  • Electronic_ISBN
    978-1-4244-2108-4
  • Type

    conf

  • DOI
    10.1109/WiCom.2008.2693
  • Filename
    4680882
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3473796