@InProceedings{wu-EtAl:2017:SemEval2,
  author    = {Wu, Guoshun  and  Sheng, Yixuan  and  Lan, Man  and  Wu, Yuanbin},
  title     = {ECNU at SemEval-2017 Task 3: Using Traditional and Deep Learning Methods to Address Community Question Answering Task},
  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     = {365--369},
  abstract  = {This paper describes the systems we submitted to the task 3 (Community Ques-
	tion Answering) in SemEval 2017 which contains three subtasks on English
	corpora,
	i.e., subtask A: Question-Comment Similarity, subtask B: Question-Question
	Similarity, and subtask C: Question-External Comment Similarity. For subtask A,
	we
	combined two different methods to represent question-comment pair, i.e.,
	supervised model using traditional features and Convolutional Neural Network.
	For subtask B, we utilized the information of snippets returned from Search
	Engine with question subject as query. For subtask C, we ranked the comments by
	multiplying the probability of the pair related question comment being Good by
	the reciprocal rank of the related question.},
  url       = {http://www.aclweb.org/anthology/S17-2060}
}