Abstract: In this journal, we aim at discovering the number of diverse user search goals for a query and depicting each goal with some keywords automatically. we propose a semantic ontology method to map feedback sessions to pseudo-documents which can efficiently reflect user information needs. At last, we cluster these pseudo documents to infer user search goals and depict them with some keywords. Since the evaluation of clustering is also an important problem, we also propose a novel evaluation criterion fuzzy score to evaluate the performance of the restructured web search results.In this paper, we propose an efficient approach to improve user search goals by analyzing search engine query logs automatically. And propose a framework to discover dissimilar user search goals for a query by clustering the proposed automatic feedback process.

Keywords: Clusters,C-Means,Metadata,Classification