@InProceedings{huang-shao-chen:2016:COLING,
  author    = {Huang, Hen-Hsen  and  Shao, Yen-Chi  and  Chen, Hsin-Hsi},
  title     = {Chinese Preposition Selection for Grammatical Error Diagnosis},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {888--899},
  abstract  = {Misuse of Chinese prepositions is one of common word usage errors in
	grammatical error diagnosis. In this paper, we adopt the Chinese Gigaword
	corpus and HSK corpus as L1 and L2 corpora, respectively. We explore gated
	recurrent neural network model (GRU), and an ensemble of GRU model and maximum
	entropy language model (GRU-ME) to select the best preposition from 43
	candidates for each test sentence. The experimental results show the advantage
	of the GRU models over simple RNN and n-gram models. We further analyze the
	effectiveness of linguistic information such as word boundary and
	part-of-speech tag in this task.},
  url       = {http://aclweb.org/anthology/C16-1085}
}