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Query classification (QC) is a task that aims to classify Web queries into topical categories. Since queries are usually short in length and ambiguous, the same query may need to be classified to different categories according to different people's perspectives. In this paper, we propose the Personalized Query Classification (PQC) task and develop an algorithm based on user preference learning as a solution. Users' preferences that are hidden in clickthrough logs are quite helpful for search
doi:10.1145/1645953.1646108
dblp:conf/cikm/CaoSXHYC09
fatcat:2d4jgxxphfbb3e4p6hbpthw2wu