谭红叶,郭少茹,陈鑫,王素格,李茹,张虎,杨陟卓, 陈千,钱揖丽,王元龙,关勇,吕国英. 高考语文阅读理解自动答题系统[J]. 中文信息学报, 2022, 36(4): 166-174.
TAN Hongye, GUO Shaoru, CHENG Xin, WANG Suge, LI Ru, ZHANG Hu, YANG Zhizhuo, CHEN Qian, QIAN Yili, WANG Yuanlong, GUAN Yong, LV Guoying. The Question Answering System for Gaokao Chinese Reading Comprehension. , 2022, 36(4): 166-174.
The Question Answering System for Gaokao Chinese Reading Comprehension
TAN Hongye1, GUO Shaoru1, CHENG Xin1, WANG Suge1, LI Ru1,2, ZHANG Hu1, YANG Zhizhuo1, CHEN Qian1, QIAN Yili1, WANG Yuanlong1, GUAN Yong1, LV Guoying1
1.School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi 030006, China; 2.Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing, Taiyuan, Shanxi 030006, China
Abstract：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.
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2022, Vol. 36 
