Exploring developments of the AI field from the perspective of methods, datasets, and metrics

doi:10.1016/j.ipm.2022.103157

	Exploring developments of the AI field from the perspective of methods, datasets, and metrics
	Yao, Rujing 1,2; Ye, Yingchun 2; Zhang, Ji3 ; Li, Shuxiao4 ; Wu, Ou2
发表期刊	INFORMATION PROCESSING & MANAGEMENT
ISSN	0306-4573
	2023-03-01
卷号	60 期号:2 页码:21
通讯作者	Wu, Ou(wuou@tju.edu.cn)
摘要	The knowledge contained in academic literature is interesting to mine. Inspired by the idea of molecular markers tracing in the field of biochemistry, three named entities, namely, methods, datasets, and metrics, are extracted and used as artificial intelligence (AI) markers for AI literature. These entities can be used to trace the research process described in the bodies of papers, which opens up new perspectives for seeking and mining more valuable academic information. Firstly, the named entity recognition model is used to extract AI markers from large-scale AI literature. A multi-stage self-paced learning strategy (MSPL) is proposed to address the negative influence of hard and noisy samples on the model training. Secondly, original papers are traced for AI markers. Statistical and propagation analyses are performed based on the tracing results. Finally, the co-occurrences of AI markers are used to achieve clustering. The evolution within method clusters is explored. The above-mentioned mining based on AI markers yields many significant findings. For example, the propagation rate of the datasets gradually increases. The methods proposed by China in recent years have an increasing influence on other countries.
关键词	AI literature Named entity recognition Self-paced learning Entity-level analysis
DOI	10.1016/j.ipm.2022.103157
关键词[WOS]	FUNCTIONAL STRUCTURE IDENTIFICATION ; NAMED ENTITY RECOGNITION ; FULL-TEXT ; ACADEMIC ARTICLES ; SOFTWARE ; CITATION ; DOMAIN
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Information Science & Library Science
WOS类目	Computer Science, Information Systems ; Information Science & Library Science
WOS记录号	WOS:000900807500017
出版者	ELSEVIER SCI LTD
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/51148
专题	复杂系统认知与决策实验室
通讯作者	Wu, Ou
作者单位	1.Nankai Univ, Business Sch, Dept Informat Resources Management, Tianjin, Peoples R China 2.Tianjin Univ, Ctr Appl Math, Tianjin, Peoples R China 3.Zhejiang Lab, Hangzhou, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Yao, Rujing,Ye, Yingchun,Zhang, Ji,et al. Exploring developments of the AI field from the perspective of methods, datasets, and metrics[J]. INFORMATION PROCESSING & MANAGEMENT,2023,60(2):21.
APA	Yao, Rujing,Ye, Yingchun,Zhang, Ji,Li, Shuxiao,&Wu, Ou.(2023).Exploring developments of the AI field from the perspective of methods, datasets, and metrics.INFORMATION PROCESSING & MANAGEMENT,60(2),21.
MLA	Yao, Rujing,et al."Exploring developments of the AI field from the perspective of methods, datasets, and metrics".INFORMATION PROCESSING & MANAGEMENT 60.2(2023):21.