计算机与数字工程2026，Vol.54Issue(1)：23-27,5.DOI:10.3969/j.issn.1672-9722.2026.01.005
基于上下文嵌入和叠加注意力的机器阅读理解
Machine Reading Comprehension Based on Context Embedding and Superimposed Attention
摘要
Abstract
Machine reading comprehension,one of the research directions of natural language processing,aims to improve the ability of computers to read and understand text content.Because the previous classical models do not consider long-term con-text dependence and polysemy,a single attention mechanism cannot fully express the meaning of the text.According to the above problems,this paper proposes an algorithm model,which improves the accuracy of word embedding by understanding the context in the embedding layer on top of the previous classical model.The accurate understanding of polysemy has a certain improvement,and the correlation between the question to the text and the text to the question is enhanced by superposition calculation,and the text meaning of attention expression is improved.On SQuAD dataset,the experimental results show that the performance of the model is significantly improved compared with the baseline model.关键词
机器阅读理解/ELMO/注意力机制/叠加注意力Key words
machine reading comprehension/ELMO/attention mechanism/superimposed attention mechanism分类
数理科学引用本文复制引用
何青山,尹祎..基于上下文嵌入和叠加注意力的机器阅读理解[J].计算机与数字工程,2026,54(1):23-27,5.基金项目
湖北省教育厅科学研究计划指导性项目(编号:B2022002)资助. （编号:B2022002）
