高考语文阅读理解自动答题系统  

The Question Answering System for Gaokao Chinese Reading Comprehension

作　　者：谭红叶[1] 郭少茹 陈鑫[1] 王素格[1] 李茹[1,2] 张虎[1] 杨陟卓[1] 陈千[1] 钱揖丽[1] 王元龙[1] 关勇 吕国英[1] TAN Hongye;GUO Shaoru;CHENG Xin;WANG Suge;LI Ru;ZHANG Hu;YANG Zhizhuo;CHEN Qian;QIAN Yili;WANG Yuanlong;GUAN Yong;LV Guoying(School of Computer and Information Technology,Shanxi University,Taiyuan,Shanxi 030006,China;Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing,Taiyuan,Shanxi 030006,China)

机构地区：[1]山西大学计算机与信息技术学院,山西太原030006 [2]计算智能与中文信息处理教育部重点实验室,山西太原030006

出　　处：《中文信息学报》2022年第4期166-174,共9页Journal of Chinese Information Processing

基　　金：国家重点研发计划项目(2018YFB1005103)。

摘　　要：机器阅读理解任务需要机器理解篇章并回答相关问题,是许多应用系统中的一项核心任务。该文面向高考语文中的现代文阅读理解文本语义表示、候选句抽取、鉴赏分析等关键技术展开研究,针对选择题、问答题等构建了相应的答题引擎,并在高考真题及测试题上,对系统进行了实验验证与错误分析,实验结果表明,该文所构建的系统能够在一定程度上解答问题。未来将围绕语义表示、知识的统一表征与知识聚合、迁移学习等前沿技术,提升阅读理解系统的复杂综合推理能力、概括分析能力、语言鉴赏能力。Machine Reading Comprehension(MRC)is a critical task in many real-world applications,which requires machines to understand a text passage and answer relevant questions.This paper studied the key technologies of textual semantic representation,candidate sentence extraction and language appreciation,and built the system for answering multiple choice questions and free-description questions.We have conducted some experiments on the Gaokao tests,finding that the system can achieve a certain degree of accuracy for both questions.In the future,we will explore to utilize more advanced techniques such as semantic representation,unified knowledge representation and aggregation,and transfer learning to improve the MRC system in complex reasoning,inductive analyzing and language appreciating.

关 键 词：高考语文 阅读理解 标准化测试 文本语义表示 候选句抽取 鉴赏分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]