User modeling in search logs via a nonparametric bayesian approach
Hongning Wang, ChengXiang Zhai, Feng Liang, Anlei Dong, Yi Chang · 2014
Searchers' information needs are diverse and cover a broad range of topics; hence, it is important for search engines to accurately understand each individual user's search intents in order to provide optimal search results. Search log data, which records users' search behaviors when interacting with search engines, provides a valuable source of information about users' search intents. Therefore, properly characterizing the heterogeneity among the users' observed search behaviors is the key to accurately understanding their search intents and to further predicting their behaviors.