Most of the search engine optimization techniques attempt to predict users interest by learning from the past information collected from different sources. But, a user's current interest often depends on many factors which are not captured in the past information. In this paper, we attempt to identify user's current interest in real time from the information provided by the user in the current query session. By identifying user's interest in real time, the engine could adapt differently to different users in real time. Experimental verification indicates that our approach is encouraging for short queries
[1]
Feng Qiu,et al.
Automatic identification of user interest for personalized search
,
2006,
WWW '06.
[2]
Zhenyu Liu,et al.
Automatic identification of user goals in Web search
,
2005,
WWW '05.
[3]
Amanda Spink,et al.
Determining the user intent of web search engine queries
,
2007,
WWW '07.
[4]
Wei-Ying Ma,et al.
Learning to cluster web search results
,
2004,
SIGIR '04.
[5]
Nega Alemayehu.
Analysis of performance variation using query expansion
,
2003,
J. Assoc. Inf. Sci. Technol..