期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：3
页码：891
DOI：10.15680/IJIRSET.2015.0403111
出版社：S&S Publications
摘要：For a broad -topic and ambiguous query, different users may have different search goals when they submit it to a search engine. The inference and analysis of user search goals can be very useful in improving search engine relevance 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 disco ver 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 a novel approach to generate pseudo-documents to better represent the feedback sessions for clustering. Finally, we propose 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 from a co mmercial search engine to validate the effectiveness of our proposed methods.
关键词：Feed Back Sessions; Click Rate Ranking; And Fuzzy Self Co nstructing Algorithm
