Improving retrieval accuracy by weighting document types with clickthrough data

For enterprise search, there exists a relationship between work task and document type that can be used to refine search results. In this poster, we adapt the popular Okapi BM25 scoring function to weight term frequency based on the relevance of a document type to a work task. Also, we use click frequency for each task-type pair to estimate a realistic weight. Using the W3C collection from the TREC Enterprise track for evaluations, our approach leads to significant improvements on search precision.