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        <title>Context-Aware Word Segmentation for Chinese Real-World Discourse</title>
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        <namePart type="given">Kaiyu</namePart>
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        <namePart type="given">Junpeng</namePart>
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            <title>Proceedings of the Second International Workshop of Discourse Processing</title>
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            <namePart type="given">Qun</namePart>
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            <namePart type="given">Xiaojun</namePart>
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    <abstract>Previous neural approaches achieve significant progress for Chinese word segmentation (CWS) as a sentence-level task, but it suffers from limitations on real-world scenario. In this paper, we address this issue with a context-aware method and optimize the solution at document-level. This paper proposes a three-step strategy to improve the performance for discourse CWS. First, the method utilizes an auxiliary segmenter to remedy the limitation on pre-segmenter. Then the context-aware algorithm computes the confidence of each split. The maximum probability path is reconstructed via this algorithm. Besides, in order to evaluate the performance in discourse, we build a new benchmark consisting of the latest news and Chinese medical articles. Extensive experiments on this benchmark show that our proposed method achieves a competitive performance on a document-level real-world scenario for CWS.</abstract>
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%0 Conference Proceedings
%T Context-Aware Word Segmentation for Chinese Real-World Discourse
%A Huang, Kaiyu
%A Liu, Junpeng
%A Cao, Jingxiang
%A Huang, Degen
%Y Liu, Qun
%Y Xiong, Deyi
%Y Ge, Shili
%Y Zhang, Xiaojun
%S Proceedings of the Second International Workshop of Discourse Processing
%D 2020
%8 December
%I Association for Computational Linguistics
%C Suzhou, China
%F huang-etal-2020-context
%X Previous neural approaches achieve significant progress for Chinese word segmentation (CWS) as a sentence-level task, but it suffers from limitations on real-world scenario. In this paper, we address this issue with a context-aware method and optimize the solution at document-level. This paper proposes a three-step strategy to improve the performance for discourse CWS. First, the method utilizes an auxiliary segmenter to remedy the limitation on pre-segmenter. Then the context-aware algorithm computes the confidence of each split. The maximum probability path is reconstructed via this algorithm. Besides, in order to evaluate the performance in discourse, we build a new benchmark consisting of the latest news and Chinese medical articles. Extensive experiments on this benchmark show that our proposed method achieves a competitive performance on a document-level real-world scenario for CWS.
%R 10.18653/v1/2020.iwdp-1.5
%U https://aclanthology.org/2020.iwdp-1.5/
%U https://doi.org/10.18653/v1/2020.iwdp-1.5
%P 22-28

Markdown (Informal)

[Context-Aware Word Segmentation for Chinese Real-World Discourse](https://aclanthology.org/2020.iwdp-1.5/) (Huang et al., iwdp 2020)

• Context-Aware Word Segmentation for Chinese Real-World Discourse (Huang et al., iwdp 2020)

ACL

• Kaiyu Huang, Junpeng Liu, Jingxiang Cao, and Degen Huang. 2020. Context-Aware Word Segmentation for Chinese Real-World Discourse. In Proceedings of the Second International Workshop of Discourse Processing, pages 22–28, Suzhou, China. Association for Computational Linguistics.