JIT_V2_N4_RP3 Ra. Radhika R. Devi Priya Journal on Information Technology 2277-5250 2 4 16 20 Clustering; EM algorithm; Genetic Algorithm; Fitness function; EvolvEM clustering Clustering is collection of data objects that are similar to one another and thus can be treated collectively as one group. The model based clustering approach uses model for clustering and optimizes the fit between the data and model. The evolutionary algorithm has the ability to thoroughly search the parameter space, providing an approach inherently more robust with respect to local maxima. In EvolvExpectation-Maximization(EvolvEM)algorithm,Expectation Maximization and Genetic algorithm is used for clustering data which shows more efficiency then EM clustering. The drawback in this method is that its execution time is higher and it requires more parameters. In the proposed approach, instead of Genetic algorithm, Bee colony optimization can be combined with Expectation Maximization algorithm in order to improve execution time and clustering efficiency. Hence, it can be efficiently used for clustering. September - November 2013 Copyright © 2013 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=2540