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
Link To Document :
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