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A Review on Question Generation from Natural Language Text

文献类型：期刊论文

作者Zhang, Ruqing1,2; Guo, Jiafeng1,2; Chen, Lu1,2; Fan, Yixing1,2; Cheng, Xueqi1,2
刊名ACM TRANSACTIONS ON INFORMATION SYSTEMS
出版日期2022
卷号40期号:1页码:43
关键词Question generation natural language generation survey
ISSN号1046-8188
DOI10.1145/3468889
英文摘要Question generation is an important yet challenging problem in Artificial Intelligence (AI), which aims to generate natural and relevant questions from various input formats, e.g., natural language text, structure database, knowledge base, and image. In this article, we focus on question generation from natural language text, which has received tremendous interest in recent years due to the widespread applications such as data augmentation for question answering systems. During the past decades, many different question generation models have been proposed, from traditional rule-based methods to advanced neural network-based methods. Since there have been a large variety of research works proposed, we believe it is the right time to summarize the current status, learn from existing methodologies, and gain some insights for future development. In contrast to existing reviews, in this survey, we try to provide a more comprehensive taxonomy of question generation tasks from three different perspectives, i.e., the types of the input context text, the target answer, and the generated question. We take a deep look into existing models from different dimensions to analyze their underlying ideas, major design principles, and training strategies We compare these models through benchmark tasks to obtain an empirical understanding of the existing techniques. Moreover, we discuss what is missing in the current literature and what are the promising and desired future directions.
资助项目National Natural Science Foundation of China (NSFC)[62006218] ; National Natural Science Foundation of China (NSFC)[61902381] ; National Natural Science Foundation of China (NSFC)[61773362] ; National Natural Science Foundation of China (NSFC)[61872338] ; Beijing Academy of Artificial Intelligence (BAAI)[BAAI2019ZD0306] ; Youth Innovation Promotion Association CAS[20144310] ; Youth Innovation Promotion Association CAS[2016102] ; Youth Innovation Promotion Association CAS[2021100] ; Lenovo-CAS Joint Lab Youth Scientist Project ; K.C. Wong Education Foundation ; Foundation and Frontier Research Key Program of Chongqing Science and Technology Commission[cstc2017jcyjBX0059]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000770678900014
出版者ASSOC COMPUTING MACHINERY
源URL[http://119.78.100.204/handle/2XEOYT63/18932]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Guo, Jiafeng
作者单位1.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China
2.Univ Chinese Acad Sci, 6 Kexueyuan South Rd, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Ruqing,Guo, Jiafeng,Chen, Lu,et al. A Review on Question Generation from Natural Language Text[J]. ACM TRANSACTIONS ON INFORMATION SYSTEMS,2022,40(1):43.
APA Zhang, Ruqing,Guo, Jiafeng,Chen, Lu,Fan, Yixing,&Cheng, Xueqi.(2022).A Review on Question Generation from Natural Language Text.ACM TRANSACTIONS ON INFORMATION SYSTEMS,40(1),43.
MLA Zhang, Ruqing,et al."A Review on Question Generation from Natural Language Text".ACM TRANSACTIONS ON INFORMATION SYSTEMS 40.1(2022):43.

入库方式： OAI收割

来源：计算技术研究所

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