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        <title>Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse</title>
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    <abstract>The task of nuclearity recognition in Chinese discourse remains challenging due to the demand for more deep semantic information. In this paper, we propose a novel text matching network (TMN) that encodes the discourse units and the paragraphs by combining Bi-LSTM and CNN to capture both global dependency information and local n-gram information. Moreover, it introduces three components of text matching, the Cosine, Bilinear and Single Layer Network, to incorporate various similarities and interactions among the discourse units. Experimental results on the Chinese Discourse TreeBank show that our proposed TMN model significantly outperforms various strong baselines in both micro-F1 and macro-F1.</abstract>
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%0 Conference Proceedings
%T Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse
%A Xu, Sheng
%A Li, Peifeng
%A Zhou, Guodong
%A Zhu, Qiaoming
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F xu-etal-2018-employing
%X The task of nuclearity recognition in Chinese discourse remains challenging due to the demand for more deep semantic information. In this paper, we propose a novel text matching network (TMN) that encodes the discourse units and the paragraphs by combining Bi-LSTM and CNN to capture both global dependency information and local n-gram information. Moreover, it introduces three components of text matching, the Cosine, Bilinear and Single Layer Network, to incorporate various similarities and interactions among the discourse units. Experimental results on the Chinese Discourse TreeBank show that our proposed TMN model significantly outperforms various strong baselines in both micro-F1 and macro-F1.
%U https://aclanthology.org/C18-1044
%P 525-535

Markdown (Informal)

[Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse](https://aclanthology.org/C18-1044) (Xu et al., COLING 2018)

• Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse (Xu et al., COLING 2018)

ACL

• Sheng Xu, Peifeng Li, Guodong Zhou, and Qiaoming Zhu. 2018. Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse. In Proceedings of the 27th International Conference on Computational Linguistics, pages 525–535, Santa Fe, New Mexico, USA. Association for Computational Linguistics.