摘要
Abstract
The question answering quality and performance are significantly enhanced by means of the answer extraction.The existing answer extraction methods suffer from the problem of interaction between questions and text information.The answer extraction model that combines context can extract the answer to a given question from the text,but this extraction method does not consider the information interaction between the text and the question.When there is only question and text data,to obtain more accurate question answers from the text,the semantic information between the question and the text can be used to predict the association between the question and the text entity.When there is only question and text data,the semantic information between the question and the text can be used to predict the association between the question and the text entity,so as to to obtain more accurate question answers from the text.On this basis,a question alignment layer and multi head attention mechanism are used to construct an information model between interactive text and questions.The experimental results show that,in comparison with the BIDAF INDEPENDENT model,the improved model has an increase of 1.281%in EM value and 1.296%in F1 value,respectively.关键词
答案抽取/问答系统/信息交互/语义信息/深度学习/多头注意力机制Key words
answer extraction/Q&A system/information exchange/semantic information/deep learning/multi head attention mechanism分类
信息技术与安全科学
