@InProceedings{zhou-EtAl:2017:EMNLP2017,
  author    = {Zhou, Hao  and  Yu, Zhenting  and  Zhang, Yue  and  Huang, Shujian  and  DAI, XIN-YU  and  Chen, Jiajun},
  title     = {Word-Context Character Embeddings for Chinese Word Segmentation},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {760--766},
  abstract  = {Neural parsers have benefited from automatically labeled data via
	dependency-context word embeddings. 
	We investigate training character embeddings on a word-based context in a
	similar way, showing that the simple method improves state-of-the-art neural
	word segmentation models significantly, beating tri-training baselines for
	leveraging auto-segmented data.},
  url       = {https://www.aclweb.org/anthology/D17-1079}
}