@InProceedings{charlet-damnati:2017:SemEval,
  author    = {Charlet, Delphine  and  Damnati, Geraldine},
  title     = {SimBow at SemEval-2017 Task 3: Soft-Cosine Semantic Similarity between Questions for Community Question Answering},
  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     = {315--319},
  abstract  = {This paper describes the SimBow system submitted at SemEval2017-Task3, for the
	question-question similarity subtask B. The proposed approach is a supervised
	combination of different unsupervised textual similarities. These textual
	similarities rely on the introduction of a relation matrix in the classical
	cosine similarity between bag-of-words, so as to get a soft-cosine that takes
	into account relations between words. According to the type of relation matrix
	embedded in the soft-cosine, semantic or lexical relations can be considered.
	Our system ranked first among the official submissions of subtask B.},
  url       = {http://www.aclweb.org/anthology/S17-2051}
}