Entity based translation language model

Abstract

Bridging the lexical gap between the user's question and the question-answer pairs in Q&A archives has been a major challenge for Q&A retrieval. State-of-the-art approaches address this issue by implicitly expanding the queries with additional words using statistical translation models. In this work we extend the lexical word based translation model to incorporate semantic concepts. We explore strategies to learn the translation probabilities between words and the concepts using the Q&A archives and Wikipedia. Experiments conducted on a large scale real data from Yahoo Answers! show that the proposed techniques are promising and need further investigation. Copyright is held by the author/owner(s).