@InProceedings{ferrero-EtAl:2017:EACLshort,
  author    = {Ferrero, J\'{e}r\'{e}my  and  Besacier, Laurent  and  Schwab, Didier  and  Agn\`{e}s, Fr\'{e}d\'{e}ric},
  title     = {Using Word Embedding for Cross-Language Plagiarism Detection},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {415--421},
  abstract  = {This paper proposes to use distributed representation of words (word
	embeddings) in cross-language textual similarity detection. The main
	contributions of this paper are the following: (a) we introduce new
	cross-language similarity detection methods based on distributed representation
	of words; (b) we combine the different methods proposed to verify their
	complementarity and finally obtain an overall F1 score of 89.15% for
	English-French similarity detection at chunk level (88.5% at sentence level) on
	a very challenging corpus.},
  url       = {http://www.aclweb.org/anthology/E17-2066}
}