@InProceedings{ferrero-EtAl:2017:SemEval,
  author    = {Ferrero, J\'{e}r\'{e}my  and  Besacier, Laurent  and  Schwab, Didier  and  Agn\`{e}s, Fr\'{e}d\'{e}ric},
  title     = {CompiLIG at SemEval-2017 Task 1: Cross-Language Plagiarism Detection Methods for Semantic Textual Similarity},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {109--114},
  abstract  = {We present our submitted systems for Semantic Textual Similarity (STS) Track 4
	at SemEval-2017. Given a pair of Spanish-English sentences, each system must
	estimate their semantic similarity by a score between 0 and 5. In our
	submission, we use syntax-based, dictionary-based, context-based, and MT-based
	methods. We also combine these methods in unsupervised and supervised way. Our
	best run ranked 1st on track 4a with a correlation of 83.02% with human
	annotations.},
  url       = {http://www.aclweb.org/anthology/S17-2012}
}