Knowledge Commons of Institute of Automation，CAS
| Exploring developments of the AI field from the perspective of methods, datasets, and metrics | |
Yao, Rujing1,2; Ye, Yingchun2; Zhang, Ji3 ; Li, Shuxiao4; Wu, Ou2
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| Source Publication | INFORMATION PROCESSING & MANAGEMENT
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| ISSN | 0306-4573 |
| 2023-03-01 | |
| Volume | 60Issue:2Pages:21 |
| Corresponding Author | Wu, Ou(wuou@tju.edu.cn) |
| Abstract | 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. |
| Keyword | AI literature Named entity recognition Self-paced learning Entity-level analysis |
| DOI | 10.1016/j.ipm.2022.103157 |
| WOS Keyword | FUNCTIONAL STRUCTURE IDENTIFICATION ; NAMED ENTITY RECOGNITION ; FULL-TEXT ; ACADEMIC ARTICLES ; SOFTWARE ; CITATION ; DOMAIN |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Computer Science ; Information Science & Library Science |
| WOS Subject | Computer Science, Information Systems ; Information Science & Library Science |
| WOS ID | WOS:000900807500017 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/51148 |
| Collection | 复杂系统认知与决策实验室 |
| Corresponding Author | Wu, Ou |
| Affiliation | 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 |
| Recommended Citation 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. |
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