%0 Journal Article
	%A Guadalupe J. Torres and  Ram B. Basnet and  Andrew H. Sung and  Srinivas Mukkamala and  Bernardete M. Ribeiro
	%D 2008
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 17, 2008
	%T A Similarity Measure for Clustering and its Applications
	%U https://publications.waset.org/pdf/9316
	%V 17
	%X This paper introduces a measure of similarity between
two clusterings of the same dataset produced by two different
algorithms, or even the same algorithm (K-means, for instance, with
different initializations usually produce different results in clustering
the same dataset). We then apply the measure to calculate the
similarity between pairs of clusterings, with special interest directed
at comparing the similarity between various machine clusterings and
human clustering of datasets. The similarity measure thus can be used
to identify the best (in terms of most similar to human) clustering
algorithm for a specific problem at hand. Experimental results
pertaining to the text categorization problem of a Portuguese corpus
(wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The
significance and other potential applications of the proposed measure
are discussed.
	%P 1712 - 1718