tailieunhanh - Báo cáo khoa học: "Phrase-Based Translation Model for Question Retrieval in Community Question Answer Archives"

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. | Phrase-Based Translation Model for Question Retrieval in Community Question Answer Archives Guangyou Zhou Li Cai Jun Zhao and Kang Liu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences 95 Zhongguancun East Road Beijing 100190 China gyzhou lcai jzhao kliu @ Abstract 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. 1 Introduction Over the past few years large scale question and answer Q A archives have become an important information resource on the Web. These include the traditional Frequently Asked Questions FAQ archives and the emerging community-based Q A services such as Yahoo Answers 1 Live QnA2 and Baidu Zhidao3. Correspondence author jzhao@ 1http 2http 3http Community-based Q A services can directly return answers to the queried questions instead of a list of relevant documents thus provide an effective alternative to the traditional adhoc information retrieval. To make full use of the large scale archives of question-answer pairs it is critical to have functionality helping users to retrieve historical answers Duan et al. 2008 . Therefore it is a meaningful task to .