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2010

Modeling Semantic Relevance for Question-Answer Pairs in Web Social Communities

9 years 1 months ago
Modeling Semantic Relevance for Question-Answer Pairs in Web Social Communities
Quantifying the semantic relevance between questions and their candidate answers is essential to answer detection in social media corpora. In this paper, a deep belief network is proposed to model the semantic relevance for question-answer pairs. Observing the textual similarity between the community-driven questionanswering (cQA) dataset and the forum dataset, we present a novel learning strategy to promote the performance of our method on the social community datasets without hand-annotating work. The experimental results show that our method outperforms the traditional approaches on both the cQA and the forum corpora.
Baoxun Wang, Xiaolong Wang, Chengjie Sun, Bingquan
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Baoxun Wang, Xiaolong Wang, Chengjie Sun, Bingquan Liu, Lin Sun
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