中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Exploring developments of the AI field from the perspective of methods, datasets, and metrics

文献类型:期刊论文

作者Yao, Rujing3,4; Ye, Yingchun3; Zhang, Ji2; Li, Shuxiao1; Wu, Ou3
刊名INFORMATION PROCESSING & MANAGEMENT
出版日期2023-03-01
卷号60期号:2页码:21
ISSN号0306-4573
关键词AI literature Named entity recognition Self-paced learning Entity-level analysis
DOI10.1016/j.ipm.2022.103157
通讯作者Wu, Ou(wuou@tju.edu.cn)
英文摘要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.
WOS关键词FUNCTIONAL STRUCTURE IDENTIFICATION ; NAMED ENTITY RECOGNITION ; FULL-TEXT ; ACADEMIC ARTICLES ; SOFTWARE ; CITATION ; DOMAIN
WOS研究方向Computer Science ; Information Science & Library Science
语种英语
出版者ELSEVIER SCI LTD
WOS记录号WOS:000900807500017
源URL[http://ir.ia.ac.cn/handle/173211/51147]  
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.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.Zhejiang Lab, Hangzhou, Peoples R China
3.Tianjin Univ, Ctr Appl Math, Tianjin, Peoples R China
4.Nankai Univ, Business Sch, Dept Informat Resources Management, Tianjin, 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.

入库方式: OAI收割

来源:自动化研究所

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