@InProceedings{rotari-EtAl:2017:SemEval,
  author    = {Rotari, R\v{a}zvan-Gabriel  and  Hulub, Ionut  and  Oprea, Stefan  and  Plamada-Onofrei, Mihaela  and  Lorent, Alina Beatrice  and  Preisler, Raluca  and  Iftene, Adrian  and  Trandabat, Diana},
  title     = {Wild Devs' at SemEval-2017 Task 2: Using Neural Networks to Discover Word 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     = {267--270},
  abstract  = {This paper presents Wild Devs’ participation in the SemEval-2017 Task 2
	“Multi-lingual and Cross-lingual Semantic Word Similarity”, which tries to
	automatically measure the semantic similarity between two words. The system was
	build using neural networks, having as input a collection of word pairs,
	whereas the output consists of a list of scores, from 0 to 4, corresponding to
	the degree of similarity between the word pairs.},
  url       = {http://www.aclweb.org/anthology/S17-2042}
}