@InProceedings{lee-EtAl:2017:I17-3,
  author    = {Lee, John  and  Liu, Meichun  and  Lam, Chun Yin  and  Lau, Tak On  and  Li, Bing  and  Li, Keying},
  title     = {Automatic Difficulty Assessment for Chinese Texts},
  booktitle = {Proceedings of the IJCNLP 2017, System Demonstrations},
  month     = {November},
  year      = {2017},
  address   = {Tapei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {45--48},
  abstract  = {We present a web-based interface that automatically assesses reading difficulty
	of Chinese texts.  The system performs word segmentation, part-of-speech
	tagging
	and dependency parsing on the input text, and then determines the difficulty
	levels of the vocabulary items and grammatical constructions in the text. 
	Furthermore, the system highlights the words and phrases that must be
	simplified or re-written in order to conform to the user-specified target
	difficulty level.  Evaluation results show that the system accurately
	identifies the vocabulary level of 89.9% of the words, and detects grammar
	points at 0.79 precision and 0.83 recall.},
  url       = {http://www.aclweb.org/anthology/I17-3012}
}