@InProceedings{bjerva-EtAl:2017:BEA,
  author    = {Bjerva, Johannes  and  Grigonyte, Gintare  and  \"{O}stling, Robert  and  Plank, Barbara},
  title     = {Neural Networks and Spelling Features for Native Language Identification},
  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     = {235--239},
  abstract  = {We present the RUG-SU team's submission at the Native Language Identification
	Shared Task 2017.
	We combine several approaches into an ensemble, based on spelling error
	features, a simple neural network using word representations, a deep residual
	network using word and character features, and a system based on a recurrent
	neural network. 
	Our best system is an ensemble of neural networks, reaching an F1 score of
	0.8323.
	Although our system is not the highest ranking one, we do outperform the
	baseline by far.},
  url       = {http://www.aclweb.org/anthology/W17-5025}
}