Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40755
Title: Exploiting salient patterns for question detection and question retrieval in community-based question answering
Authors: Wang, K. 
Chua, T.-S. 
Issue Date: 2010
Source: Wang, K.,Chua, T.-S. (2010). Exploiting salient patterns for question detection and question retrieval in community-based question answering. Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference 2 : 1155-1163. ScholarBank@NUS Repository.
Abstract: 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. Online questions are usually long and informal, and standard features such as question mark or 5W1H words are likely to be absent. In this paper, we explore question 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 detecting online question sentences, and it considerably boosts the question retrieval performance in cQA.
Source Title: Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/40755
Appears in Collections:Staff Publications

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