A Review on Question Generation from Natural Language Text

doi:10.1145/3468889

	A Review on Question Generation from Natural Language Text
	Zhang, Ruqing 1,2; Guo, Jiafeng 1,2; Chen, Lu 1,2; Fan, Yixing 1,2; Cheng, Xueqi 1,2
	2022
发表期刊	ACM TRANSACTIONS ON INFORMATION SYSTEMS
ISSN	1046-8188
卷号	40 期号:1 页码:43
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.
关键词	Question generation natural language generation survey
DOI	10.1145/3468889
收录类别	SCI
语种	英语
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
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000770678900014
出版者	ASSOC COMPUTING MACHINERY
引用统计	被引频次：23[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/18933
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.