document: Probabilistic query expansion using query logs Query expansion has long been suggested as an effective way to resolve the short query and word mismatching problems . A number of query expansion methods have been proposed in traditional information retrieval . However , these previous methods do not take into account the specific characteristics of web searching ; in particular , of the availability of large amount of user interaction information recorded in the web query logs . In this study , we propose a new method for query expansion based on query logs . The central idea is to extract probabilistic correlations between query terms and document terms by analyzing query logs . These correlations are then used to select high-quality expansion terms for new queries . The experimental results show that our log-based probabilistic query expansion method can greatly improve the search performance and has several advantages over other existing methods .
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