• DocumentCode
    1796334
  • Title

    Quantum clustering — A novel method for text analysis

  • Author

    Ding Liu ; Minghu Jiang ; Xiaofang Yang

  • Author_Institution
    Sch. of Comput. Sci. & Software Eng., Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    17
  • Lastpage
    23
  • Abstract
    The article introduces quantum clustering inspired from the quantum mechanics and extended to text analysis. This novel method upgrades the nonparametric density estimation and, different from the latter, quantum clustering constructs the potential function to determine the cluster center instead of the Gaussian kernel function. The result of a comparative experiment proves the advantage of quantum clustering over the conventional Parzen-window, and the further trial on authorship identification illustrates the wide application scope of this novel method.
  • Keywords
    estimation theory; nonparametric statistics; pattern clustering; text analysis; authorship identification; nonparametric density estimation; quantum clustering; quantum mechanics; text analysis; Clustering algorithms; Educational institutions; Electric potential; Equations; Kernel; Mathematical model; Quantum mechanics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CIDM.2014.7008143
  • Filename
    7008143