A Novel Approach for Inferring and Analyzing User Search Goals

With exponentially, increasing information becoming available on the Internet, Web search has become an indispensable tool for Web users to gain desired information. Typically, Web users submit a short Web query consisting of a few words to search engines. Because these queries are short and ambiguous, how to interpret he queries in terms of a set of target categories has become a major research issue. The inference and analysis of user search goals can have a lot of advantages in improving search engine relevance and user experience. It enhances the quality and delivery of internet information services to the end user, and improves Web server system performance. Query classification, search result reorganization, and session boundary detection, approaches attempt to infer user search goals [6] and intent, but has many limitations. In this paper we propose a novel approach that overcomes the limitations and analyze, infer user search goals using feedback sessions.