K. Srinivasa Rao
Different users may have different search goals when they submit it to a search engine. If we know the user search goals means we can easily improve their searching and user experience. In this paper, we propose a novel approach to infer user search goals by analyzing search engine query logs. First, we propose a framework to discover different user search goals for a query by clustering the proposed feedback sessions. Feedback sessions are constructed from user click-through logs and can efficiently reflect the information needs of users. Second, we propose novel approach togenerate pseudo-documents to better represent the feedback sessions for clustering. Finally, we proposed a new criterion “Classified Average Precision (CAP)”to evaluate the performance of inferring user search goals. Experimental results are presented using user click-through logs.
Search Engine Query