Abstract
Web queries clustering attract great concern recently. It is crucial for capturing frequently asked questions in question-answering system, most popular topics in search engine or automatic query expansion in information retrieval. The paper presents a new algorithm of web queries clustering using user click information in the query logs and applies it into query expansion. Different from previous work, in the new algorithm both word form and semantic information have been taken into considered. Experiments show that the new algorithm works effectively.
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