选择式机器阅读理解综述

Review of multi-choice machine reading comprehension

机器阅读理解是自然语言处理领域的研究热点之一,对提升机器阅读能力和智能水平有着重要意义,为跟进相关领域的研究进展对其进行综述。首先,介绍机器阅读理解的发展历程及主要任务;其次,重点梳理当前选择式机器阅读理解基于深度学习方法的相关工作,并从语义匹配、预训练模型、语义推理、外部知识四个方面展开叙述;归纳总结了相关数据集以及评价指标;最后,对选择式机器阅读理解的未来发展趋势进行了展望。

Machine reading comprehension is one of the research hotspots in the field of natural language processing,it is of great significance to improve the reading ability and intelligence level of the machine.In order to follow up the research progress in related fields,this paper reviewed it.Firstly,this paper introduced the development process and main tasks of machine reading comprehension.Secondly,it focused on the current work of multi-choice machine reading comprehension based on deep learning methods,and described the related work from four aspects:semantic matching,pre-training model,semantic reasoning and external knowledge.Next,it summarized the related datasets and evaluation metrics.Finally,this paper looked forward to the future development trend of multi-choice machine reading comprehension.