跳到主要导航 跳到搜索 跳到主要内容

ECNU at 2016 LiveQA Track: A Parameter Sharing Long Short Term Memory Model for Learning Question Similarity

  • Weijie An
  • , Mengfei Shi
  • , Xin Ouyang
  • , Yan Yang
  • , Qinmin Hu
  • , Liang He

科研成果: 会议稿件论文同行评审

摘要

In this paper, we present our system which is evaluated in the TREC 2016 LiveQA Challenge. Same as the last year, the TREC 2016 LiveQA track focuses on “live” question answering for the real-user questions from Yahoo! Answer. In this year, we first apply a parameter sharing Long Short Term Memory(LSTM) network to learn a high embedding of question representation. Then we combine the question representation with the key words information to strengthen the representation of semantic-similar questions, followed by calculating the question similarity with a simple metric function. Our approach outperforms the average score of all submitted runs.

源语言英语
出版状态已出版 - 2016
活动25th Text REtrieval Conference, TREC 2016 - Gaithersburg, 美国
期限: 15 11月 201618 11月 2016

会议

会议25th Text REtrieval Conference, TREC 2016
国家/地区美国
Gaithersburg
时期15/11/1618/11/16

指纹

探究 'ECNU at 2016 LiveQA Track: A Parameter Sharing Long Short Term Memory Model for Learning Question Similarity' 的科研主题。它们共同构成独一无二的指纹。

引用此