边宁,韩先培,何苯,孙乐. 面向高考历史科目试题的自动答题系统[J]. 中文信息学报, 2022, 36(4): 137-145.
BIAN Ning, HAN Xianpei, HE Ben, SUN Le. Automatic Question Answering System for History Subject of National College Entrance Examination. , 2022, 36(4): 137-145.
Automatic Question Answering System for History Subject of National College Entrance Examination
BIAN Ning1,2, HAN Xianpei2, HE Ben1,2, SUN Le2
1.School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China; 2.Chinese Information Processing Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
Abstract：The National College Entrance Examination is a standardized test that comprehensively evaluates the level of human knowledge and abilities, which serves as a more challenging question answering task. This paper designs an automatic question answering system for the history subject of National College Entrance Examination based on deep neural networks. One of the challenges for knowledge-enhanced question answering is the contextual sensitivity of knowledge: among the large amount of knowledge stored in the knowledge base, only a few pieces of knowledge are relevant to answering a certain question. In response to this challenge, this paper designs a knowledge-enhanced question answering system that combines knowledge retrieval and machine reading comprehension. Through the relevance ranking ability of the knowledge retrieval system and the knowledge positioning ability of the machine reading comprehension model, knowledge related to the question can be effectively discovered, thereby enhancing the performance of the question answering system. The experimental results show that the system can effectively answer questions in the history subject of National College Entrance Examination.
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