@InProceedings{mohammadi-veisi-amini:2017:BEA,
  author    = {Mohammadi, Elham  and  Veisi, Hadi  and  Amini, Hessam},
  title     = {Native Language Identification Using a Mixture of Character and Word N-grams},
  booktitle = {Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {210--216},
  abstract  = {Native language identification (NLI) is the task of determining an author's
	native language, based on a piece of his/her writing in a second language. In
	recent years, NLI has received much attention due to its challenging nature and
	its applications in language pedagogy and forensic linguistics. We participated
	in the NLI2017 shared task under the name UT-DSP. In our effort to implement a
	method for native language identification, we made use of a fusion of character
	and word N-grams, and achieved an optimal F1-Score of 77.64\%, using both essay
	and speech transcription datasets.},
  url       = {http://www.aclweb.org/anthology/W17-5022}
}