Deducing User Seek Goals with Feedback Series Using Fuzzy Self Constructing Algorithm
Hod Cse · 2014
An ambiguous query, various users may have distinct search goals when they enter in to a search engine. The deducing and analysis of user search goals can be very useful in improving search engine relevance and user experience. In this paper, I propose a novel approach to deduce user search goals by analysing search engine query logs. First, I propose a framework to discover various user search goals for a query by clumping the proposed feedback sessions. Feedback sessions are constructed from user click-through logs and can efficiently reflect the information needs of users. Second, I propose a novel approach to generate pseudo-documents to better represent the feedback sessions for clumping. Finally, I propose a new criterion “Classified Average Precision (CAP)” to evaluate the performance of deducing user search goals. Experimental results are presented using user click-through logs from a commercial search engine to validate the effectiveness of our proposed methods.