A method of Web search result clustering based on rough sets

Due to the enormous size of the Web and low precision of user queries, finding the right information from the Web can be difficult if not impossible. One approach that tries to solve this problem is using clustering techniques for grouping similar document together in order to facilitate presentation of results in more compact form and enable thematic browsing of the results set. The main problem of many Web search result (snippet) clustering algorithm is based on the poor vector representation of snippets. In this paper, we present a method of snippet representation enrichment using tolerance rough set model. We applied the proposed method to construct a rough set based search result clustering algorithm and compared it with other recent methods.