@InProceedings{lin-chen:2018:NLPTEA,
  author    = {Lin, Chuan-Jie  and  Chen, Shao-Heng},
  title     = {Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences},
  booktitle = {Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {203--206},
  abstract  = {The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.},
  url       = {http://www.aclweb.org/anthology/W18-3730}
}