@InProceedings{bjerva-ostling:2017:SemEval,
  author    = {Bjerva, Johannes  and  \"{O}stling, Robert},
  title     = {ResSim at SemEval-2017 Task 1: Multilingual Word Representations 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     = {154--158},
  abstract  = {Shared Task 1 at SemEval-2017 deals with assessing the semantic similarity
	between sentences, either in the same or in different languages.
	In our system submission, we employ multilingual word representations, in which
	similar words in different languages are close to one another.
	Using such representations is advantageous, since the increasing amount of
	available parallel data allows for the application of such methods to many of
	the languages in the world.
	Hence, semantic similarity can be inferred even for languages for which no
	annotated data exists.
	Our system is trained and evaluated on all language pairs included in the
	shared task (English, Spanish, Arabic, and Turkish).
	Although development results are promising, our system does not yield high
	performance on the shared task test sets.},
  url       = {http://www.aclweb.org/anthology/S17-2021}
}