Evaluating verbose query processing techniques

Verbose or long queries are a small but significant part of the query stream in web search, and are common in other applications such as collaborative question answering (CQA). Current search engines perform well with keyword queries but are not, in general, effective for verbose queries. In this paper, we examine query processing techniques which can be applied to verbose queries prior to submission to a search engine in order to improve the search engine's results. We focus on verbose queries that have sentence-like structure, but are not simple "wh-" questions, and assume the search engine is a "black box." We evaluated the output of two search engines using queries from a CQA service and our results show that, among a broad range of techniques, the most effective approach is to simply reduce the length of the query. This can be achieved effectively by removing "stop structure" instead of only stop words. We show that the process of learning and removing stop structure from a query can be effectively automated.