@InProceedings{liu-EtAl:2016:NLPTEA2016,
  author    = {Liu, Yajun  and  Han, Yingjie  and  Zhuo, Liyan  and  Zan, Hongying},
  title     = {Automatic Grammatical Error Detection for Chinese based on Conditional Random Field},
  booktitle = {Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {57--62},
  abstract  = {In the process of learning and using Chinese, foreigners may have grammatical
	errors due to negative migration of their native languages. Currently, the
	computer-oriented automatic detection method of grammatical errors is not
	mature enough. Based on the evaluating task ----CGED2016, we select and analyze
	the classification model and design feature extraction method to obtain
	grammatical errors in-cluding Mission(M), Disorder(W), Selection (S) and
	Redundant (R) automatically. The experiment re-sults based on the dynamic
	corpus of HSK show that the Chinese grammatical error automatic detection
	method, which uses CRF as classification model and n-gram as feature extraction
	method. It is simple and efficient whichplay a positive effect on the research
	of Chinese grammatical error automatic detection and also a supporting and
	guiding role in the teaching of Chinese as a foreign language.},
  url       = {http://aclweb.org/anthology/W16-4908}
}