@InProceedings{galbraith-pratap-shank:2017:SemEval,
  author    = {Galbraith, Byron  and  Pratap, Bhanu  and  Shank, Daniel},
  title     = {Talla at SemEval-2017 Task 3: Identifying Similar Questions Through Paraphrase Detection},
  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     = {375--379},
  abstract  = {This paper describes our approach to the SemEval-2017 shared task of
	determining question-question similarity in a community question-answering
	setting (Task 3B). We extracted both syntactic and semantic similarity features
	between candidate questions, performed pairwise-preference learning to optimize
	for ranking order, and then trained a random forest classifier to predict
	whether the candidate questions are paraphrases of each other. This approach
	achieved a MAP of 45.7% out of max achievable 67.0% on the test set.},
  url       = {http://www.aclweb.org/anthology/S17-2062}
}