CSIM: a document clustering algorithm based on swarm intelligence
Bin Lin Wu, Zheng Yi, Liu Shaohui, Zhongzhi Shi · 2003
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.