Machine Reading Comprehension Based On Multi-headed attention Model

摘要：

　　Machine Reading Comprehension(MRC)refers to the task that aims to read the context through the machine and answer the question about the original text,which needs to be modeled in the interaction between the context and the question.Recently,attention mechanisms in deep learning have been successfully extended to MRC tasks.In general,the attention-based approach is to focus attention on a small part of the context and to generalize it using a fixed-size vector.This paper introduces a network of attention from coarse to fine,which is a multi-stage hierarchical process.Firstly,the context and questions are encoded by bi-directional LSTM RNN; Then,more accurate interaction information is obtained after multiple iterations of the attention mechanism; Finally,a cursor-based approach is used to predicts the answer at the beginning and end of the original text.Experimental evaluation of shows that the BiDMF(Bi-Directional Multi-Attention Flow)model designed in this paper achieved 34.1%BLUE4 value and 39.5%Rouge-L value on the test set.

作者: Hui Xu Shichang Zhang Jie Jiang

作者单位: College of Systems Engineering,National University of Defense Technology,410073 Changsha,China School of Information Science and Engineering,Ocean University of China,Songling Road No.238,266100

会议类型: 国际会议

会议名称: 2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)(2018第二届电子信息技术与计算机工程国际会议)(EITCE2018)

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）