@InProceedings{huang-peinelt-ku:2016:COLINGDEMO,
  author    = {Huang, Chieh-Yang  and  Peinelt, Nicole  and  Ku, Lun-Wei},
  title     = {Automatically Suggesting Example Sentences of Near-Synonyms for Language Learners},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {302--306},
  abstract  = {In this paper, we propose GiveMeExample that ranks example sentences according
	to
	their capacity of demonstrating the differences among English and Chinese
	near-synonyms for language learners. The difficulty of the example sentences is
	automatically detected. Furthermore, the usage models of the near-synonyms are
	built by the GMM and Bi-LSTM models to suggest the best elaborative sentences.
	Experiments show the good performance both in the fill-in-the-blank test and on
	the manually labeled gold data, that is, the built models can select the
	appropriate words for the given context and vice versa.},
  url       = {http://aclweb.org/anthology/C16-2063}
}