%0 Journal Article %T Experimental Estimation of Number of Clusters Based on Cluster Quality %A Grace, G. Hannah %A Desikan, Kalyani %J Journal of Mathematics and Computer Science %D 2014 %V 12 %N 4 %@ ISSN 2008-949X %F Grace2014 %X Text Clustering is a text mining technique which divides the given set of text documents into significant clusters. It is used for organizing a huge number of text documents into a well-organized form. In the majority of the clustering algorithms, the number of clusters must be specified apriori, which is a drawback of these algorithms. The aim of this paper is to show experimentally how to determine the number of clusters based on cluster quality. Since partitional clustering algorithms are well-suited for clustering large document datasets, we have confined our analysis to a partitional clustering algorithm. %9 journal article %R 10.22436/jmcs.012.04.06 %U http://dx.doi.org/10.22436/jmcs.012.04.06 %P 304-315