Using Key Concepts in a Translation Model for Retrieval

Many queries, especially those in the form of longer questions, contain a subset of terms representing key concepts that describe the most important part of the user's information need. Detecting the key concepts in a query can be used as the basis for more effective weighting of query terms, but in this paper, we focus on a method of using the key concepts in a translation model for query expansion and retrieval. Translation models have been used previously in community-based question answering (CQA) systems in order to bridge the semantic gap between questions and the corresponding answer documents. Our method uses the key concepts of a question as the translation context and selectively applies the translation model to the secondary (non-key) parts of the question. We evaluate the proposed method using a CQA collection and show that selectively translating key and secondary concepts can significantly improve the retrieval performance compared to a baseline that applies the translation model without considering key concepts.