As we countdown to the annual Lucene/Solr Revolution conference in Las Vegas next month, we’re highlighting talks and sessions from past conferences. Today, we’re highlighting Target’s Howard Wan’s talk, “Using A Query Classifier To Dynamically Boost Solr Ranking”.

About 40% of our queries at are ambiguous, which can result in products from many categories. For example, the query “red apple” can match the following products: a red apple ipod (electronic category), red apple fruit ( fresh produce ), red apple iphone case ( accessories). It is desirable to have a classifier to instruct Solr to boost items from the desire category. In addition, for a search engine with a small index, a good percentage of the queries may have little or no results. Is it possible to use the classifier to solve both problems? This talk discusses a classifier built from behavior data which can dynamically re-classify the query to solve both problems.

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