@InProceedings{feng-EtAl:2017:SemEval,
  author    = {Feng, Wenzheng  and  Wu, Yu  and  Wu, Wei  and  Li, Zhoujun  and  Zhou, Ming},
  title     = {Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features 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     = {280--286},
  abstract  = {This paper presents the system in SemEval-2017 Task 3, Community Question
	Answering (CQA). We develop a ranking system that is capable of capturing
	semantic relations between text pairs with little word overlap.  In addition to
	traditional NLP features, we introduce several neural network based matching
	features which enable our system to measure text similarity beyond lexicons.
	Our system significantly outperforms baseline methods and holds the second
	place in Subtask A and the fifth place in Subtask B, which demonstrates its
	efficacy on answer selection and question retrieval.},
  url       = {http://www.aclweb.org/anthology/S17-2045}
}