Abstract:
Cluster analysis is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. Clustering categorical data is an important re...Show MoreMetadata
Abstract:
Cluster analysis is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. Clustering categorical data is an important research area data mining. In this paper we propose a novel algorithm to cluster categorical data. Based on the minimum dissimilarity value objects are grouped into cluster. In the merging process, the objects are relocated using silhouette coefficient. Experimental results show that the proposed method is efficient.
Published in: International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007)
Date of Conference: 13-15 December 2007
Date Added to IEEE Xplore: 07 January 2008
Print ISBN:0-7695-3050-8