Recent Advances in Cluster Analysis
The purpose of this paper is to provide a review of the issues related to cluster analysis, one of the most important and primitive activities of human beings, and of the advances made in recent years.
The paper investigates the clustering algorithms rooted in machine learning, computer science, statistics, and computational intelligence.
The paper reviews the basic issues of cluster analysis and discusses the recent advances of clustering algorithms in scalability, robustness, visualization, irregular cluster shape detection, and so on.
The paper presents a comprehensive and systematic survey of cluster analysis and emphasizes its recent efforts in order to meet the challenges caused by the glut of complicated data from a wide variety of communities.
R. Xu and D. C. Wunsch, "Recent Advances in Cluster Analysis," International Journal of Intelligent Computing and Cybernetics, vol. 1, no. 4, pp. 484-508, Emerald, Jan 2008.
The definitive version is available at http://dx.doi.org/10.1108/17563780810919087
Electrical and Computer Engineering
International Standard Serial Number (ISSN)
Article - Journal
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