%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. %U https://aclanthology.org/2020.iwdp-1.5 %P 22-28