• DocumentCode
    1652984
  • Title

    CSIM: a document clustering algorithm based on swarm intelligence

  • Author

    Bin, Wu ; Yi, Zheng ; Shaohui, Liu ; Zhongzhi, Shi

  • Author_Institution
    Key Lab. of Intelligent Inf. Process., Chinese Acad. of Sci., China
  • Volume
    1
  • fYear
    2002
  • Firstpage
    477
  • Lastpage
    482
  • Abstract
    This paper presents a document clustering algorithm based on swarm intelligence and k-means: CSIM. First, a document clustering algorithm based on swarm intelligence is employed. It is derived from a basic model interpreting ant colony organization of cemeteries. Swarm intelligence for flexibility, self-organization and robustness has been applied in a variety of areas. Taking advantage of these traits, good initial clusters are obtained in the first phase in CSIM. We then combine it with the classical k-means clustering method by using the clusters as initial centers. CSIM inherits the prominent properties of both swarm intelligence and k-means. It also offsets the weakness of those two techniques. Experimental results show the good performance of the hybrid document clustering algorithm
  • Keywords
    document handling; information resources; information retrieval; pattern clustering; self-adjusting systems; CSIM; ant colony organization; cemeteries; document clustering algorithm; flexibility; k-means; k-means clustering method; robustness; self-organization; swarm intelligence; Animals; Clustering algorithms; Clustering methods; Computers; Information processing; Insects; Laboratories; Particle swarm optimization; Robustness; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1006281
  • Filename
    1006281