• DocumentCode
    1812002
  • Title

    Research of Similarity Measurements in the Clustering Analysis

  • Author

    Li, LiuBai ; Hongyao, Deng

  • Author_Institution
    Coll. of Math. & Comput. Sci., Yangtze Normal Univ., Chongqing, China
  • fYear
    2010
  • fDate
    24-25 July 2010
  • Firstpage
    3
  • Lastpage
    6
  • Abstract
    Similarity measurements play an important role in the clustering analysis, so any good or bad methods of measuring similar degree directly affect the clustering algorithm. In the paper, several approaches to similarity measurements for single attribute type data, which had been proposed, have been discussed. Moreover, a way has been obtained so as to calculate the similar degree of multiple attribute type data. At last a experiment was tested. The result shows that the method is not only feasible but also effective.
  • Keywords
    pattern clustering; clustering analysis; multiple attribute type data; similar degree measurement; similarity measurement; single attribute type data; Algorithm design and analysis; Clustering algorithms; Correlation; Equations; Euclidean distance; Mathematical model; White blood cells; attribute type; clustering; distance andcoefficient; similarity measurements;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Computer Science (ITCS), 2010 Second International Conference on
  • Conference_Location
    Kiev
  • Print_ISBN
    978-1-4244-7293-2
  • Electronic_ISBN
    978-1-4244-7294-9
  • Type

    conf

  • DOI
    10.1109/ITCS.2010.9
  • Filename
    5557341