Abstract
The gap between user search intents and search results is an important issue. Grouping terms according to semantics seems to be a good way bridging the semantic gap between the user and the search engine. We propose a framework to extract semantic concepts through grouping queries using a clustering technique. To represent and discover the semantics of a query, we utilized a Web directory and social annotations (tags). In addition, we built hierarchies between concepts by splitting and merging clusters iteratively. Through exploiting expert wisdom from Web taxonomy and crowd wisdom from collaborative folksonomy, the experiment results show that our framework is effective.