2010 , Volume 15, № 2, p.3-14

Document clustering algorithms play important role in helping users to get relevant information, navigate, summarize and organize an enormous amount of textual document available on the Internet, and in digital libraries, news sources, and company-wide intranets. The objective of our work is to develop a high quality criterion functions for partitional document collection. In present paper we introduce two weighted criterion functions. We've also proposed a modified differential evolution algorithm to optimize the criterion functions. The proposed methods experimentally were evaluated onlinebreak WebKb dataset. Experiments showed that the weighted criterion functions outperform the results obtained by the unweighted criterion functions.