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→How to adapt the changes of the queries and categories over time?: === Adapting to changes of the queries and categories over time === |
→How to use the unlabeled query logs to help with query classification?: === Using unlabeled query logs to help with query classification === |
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Intermediate taxonomy based method<ref>Shen et al. [http://portal.acm.org/ft_gateway.cfm?id=1148196 "Building bridges for web query classification"]. ''ACM SIGIR, 2006''.</ref> first builds a bridging classifier on an intermediate taxonomy, such as [[Open Directory Project]] (ODP), in an offline mode. This classifier is then used in an online mode to map user queries to the target categories via the intermediate taxonomy. The advantage of this approach is that the bridging classifier needs to be trained only once and is adaptive for each new set of target categories and incoming queries.
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Since the manually labeled training data for query classification is expensive, how to use a very large web search engine query log as a source of unlabeled data to aid in automatic query classification becomes a hot issue. These logs record the Web users' behavior when they search for information via a search engine. Over the years, query logs have become a rich resource which contains Web users' knowledge about the World Wide Web.
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