• DocumentCode
    2370322
  • Title

    Fast PNN-based clustering using k-nearest neighbor graph

  • Author

    Fränti, Pasi ; Virmajoki, Olli ; Hautamäki, Ville

  • Author_Institution
    Dept. of Comput. Sci., Joensuu Univ., Finland
  • fYear
    2003
  • fDate
    19-22 Nov. 2003
  • Firstpage
    525
  • Lastpage
    528
  • Abstract
    Search for nearest neighbor is the main source of computation in most clustering algorithms. We propose the use of nearest neighbor graph for reducing the number of candidates. The number of distance calculations per search can be reduced from O(N) to O(k) or where N is the number of clusters, and k is the number of neighbors in the graph. We apply the proposed scheme within agglomerative clustering algorithm known as the PNN algorithm.
  • Keywords
    graph theory; search problems; statistical analysis; vector quantisation; PNN; agglomerative clustering algorithm; k-nearest neighbor graph; pairwise nearest neighbor; search problem; vector quantization; Clustering algorithms; Computer science; Costs; Distortion measurement; Iterative algorithms; Mean square error methods; Nearest neighbor searches; Optimization methods; Tree graphs; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
  • Print_ISBN
    0-7695-1978-4
  • Type

    conf

  • DOI
    10.1109/ICDM.2003.1250968
  • Filename
    1250968