Exploiting Bilingual Translation for Question Retrieval in Community-Based Question Answering.

Community-based question answering (CQA) has become an important issue due to the popularity of CQA archives on the web. This paper is concerned with the problem of question retrieval. Question retrieval in CQA archives aims to find historical questions that are semantically equivalent or relevant to the queried questions. However, question retrieval is challenging partly due to the word ambiguity and lexical gap between the queried questions and the historical questions in the archives. To deal with these problems, we propose the use of translated words to enrich the question representation, going beyond the words in the original language to represent a question. In this paper, each original language question (e.g., English) is automatically translated into an foreign language (e.g., Chinese) by machine translation services, and the resulting translated questions serves as a semantically enhanced representation for supplementing the original bag of words. Experiments conducted on real CQA data set demonstrate that our proposed approach significantly outperforms several baseline methods and achieves the state-of-the-art performance. © 2012 The COLING.