@InProceedings{cianflone-kosseim:2016:VarDial3,
  author    = {Cianflone, Andre  and  Kosseim, Leila},
  title     = {N-gram and Neural Language Models for Discriminating Similar Languages},
  booktitle = {Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {243--250},
  abstract  = {This paper describes our submission to the 2016 Discriminating Similar
	Languages (DSL) Shared Task. We participated in the closed Sub-task 1 with two
	separate machine learning techniques. The first approach is a character based
	Convolution Neural Network with an LSTM layer (CLSTM), which achieved an
	accuracy of 78.45\% with minimal tuning.  The second approach is a
	character-based n-gram model of size 7. It achieved an accuracy of 88.45\%
	which is close to the accuracy of 89.38\% achieved by the best submission.},
  url       = {http://aclweb.org/anthology/W16-4831}
}