Browse > Article
http://dx.doi.org/10.5351/CKSS.2012.19.2.213

Fuzzy k-Means Local Centers of the Social Networks  

Woo, Won-Seok (Department of Statistics, Korea University)
Huh, Myung-Hoe (Department of Statistics, Korea University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.2, 2012 , pp. 213-217 More about this Journal
Abstract
Fuzzy k-means clustering is an attractive alternative to the ordinary k-means clustering in analyzing multivariate data. Fuzzy versions yield more natural output by allowing overlapped k groups. In this study, we modify a fuzzy k-means clustering algorithm to be used for undirected social networks, apply the algorithm to both real and simulated cases, and report the results.
Keywords
Fuzzy k-means clustering; social network analysis; local centers; communities;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York.
2 Dunn, J. C. (1973). A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters, Journal of Cybernetics, 3, 32-57.   DOI
3 Goodreau, S. M., Handcock, M. S., Hunter, D. R., Butts, C. T. and Morris, M. (2008). A statnet tutorial, Journal of Statistical Software, 24, 1-26.
4 Huh, M. H. (2011). Local centers of the social network, Communications of the Korean Statistical Society, 18, 213-217.   과학기술학회마을   DOI   ScienceOn
5 Huh, M. H. and Lee, Y. (2011). Random generation of the social network with several communities, Communications of the Korean Statistical Society, 18, 595-601.   과학기술학회마을   DOI   ScienceOn
6 Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M. and Morris, M. (2008). ergm: A pack-age to fit, simulate and diagnose exponential-family models for networks, Journal of Statistical Software, 24, 1-29.
7 Zachary, W. W. (1978). An information flow model for conflict and fission in small groups, Journal of Anthropological Research, 33, 452-473.