Paper: Exploiting Salient Patterns for Question Detection and Question Retrieval in Community-based Question Answering

ACL ID C10-1130
Title Exploiting Salient Patterns for Question Detection and Question Retrieval in Community-based Question Answering
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Question detection serves great purposes in the cQA question retrieval task. While detecting questions in standard language data corpus is relatively easy, it becomes a great challenge for online content. On- line questions are usually long and infor- mal, and standard features such as ques- tion mark or 5W1H words are likely to be absent. In this paper, we explore ques- tion characteristics in cQA services, and propose an automated approach to detect question sentences based on lexical and syntactic features. Our model is capable of handling informal online languages. The empirical evaluation results further demonstrate that our model significantly outperforms traditional methods in de- tecting online question sentences, and it considerably boosts the question retrieval performance in cQA...