Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering
2017-08-01SEMEVAL 2017Unverified0· sign in to hype
Wenzheng Feng, Yu Wu, Wei Wu, Zhoujun Li, Ming Zhou
Unverified — Be the first to reproduce this paper.
ReproduceAbstract
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.