title: Generating personalized web search using semantic context.
abstract: The "one size fits the all" criticism of search engines is that when queries are submitted, the same results are returned to different users. In order to solve this problem, personalized search is proposed, since it can provide different search results based upon the preferences of users. However, existing methods concentrate more on the long-term and independent user profile, and thus reduce the effectiveness of personalized search. In this paper, the method captures the user context to provide accurate preferences of users for effectively personalized search. First, the short-term query context is generated to identify related concepts of the query. Second, the user context is generated based on the click through data of users. Finally, a forgetting factor is introduced to merge the independent user context in a user session, which maintains the evolution of user preferences. Experimental results fully confirm that our approach can successfully represent user context according to individual user information needs.
authors.affiliation: The Third Research Institute, Ministry of Public Security, Shanghai 201142, China ; Tsinghua University, Beijing 100081, China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Xu
authors.affiliation: East China University of Political Science and Law, Shanghai 201142, China.
authors.forename: Hai-Yan
authors.initials: HY
authors.lastname: Chen
authors.affiliation: Shanghai University, Shanghai 201142, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Yu