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An Ensemble Clustering Algorithm based on a Prior Knowledge  

Ko, Song (중앙대학교 컴퓨터공학과)
Kim, Dae-Won (중앙대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.2, 2009 , pp. 109-121 More about this Journal
Abstract
Although a prior knowledge is a factor to improve the clustering performance, it is dependant on how to use of them. Especial1y, when the prior knowledge is employed in constructing initial centroids of cluster groups, there should be concerned of similarities of a prior knowledge. Despite labels of some objects of a prior knowledge are identical, the objects whose similarities are low should be separated. By separating them, centroids of initial group were not fallen in a problem which is collision of objects with low similarities. There can use the separated prior knowledge by various methods such as various initializations. To apply association rule, proposed method makes enough cluster group number, then the centroids of initial groups could constructed by separated prior knowledge. Then ensemble of the various results outperforms what can not be separated.
Keywords
clustering; semi-supervised; ensemble method; association rule;
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