International Journal of Advanced Technology in Engineering and Science (IJATES)
The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. In data mining, clustering can be done offline to extract usage patterns and give recommendations that are highly dependent on the quality of clustering solution. Evolutionary clustering is a research area addressing the problem of clustering time stamped data. In this paper, propose an algorithm for evolutionary clustering using Weka. A variance score based approach for evolutionary clustering must satisfy the two criteria of evolutionary clustering. This paper provides theoretical as well as experimental proofs to support claims.