Community-based question answer (Q&A) has become an important issue due to the popularity of Q&A archives on the web. This paper is concerned with the problem of question retrieval. Question retrieval in Q&A archives aims to find historical questions that are semantically equivalent or relevant to the queried questions. In this paper, we propose a novel phrase-based translation model for question retrieval. Compared to the traditional word-based translation models, the phrasebased translation model is more effective because it captures contextual information in modeling the translation of phrases as a whole, rather than translating single words in isolation. Experiments conducted on real Q&A data demonstrate that our proposed phrasebased translation model significantly outperforms the state-of-the-art word-based translation model.
Within this context, Zhou et al. REF tried to improve the word-based translation model by adding some contextual information when translating the phrases as a whole, instead of translating separate words.
Phrase-Based Translation Model for Question Retrieval in Community Question Answer Archives
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
Computer Science