摘 要: 为了深度剖析国际人工智能的研究现状和前沿趋势,准确了解世界人工智能研究的发展阶段和特点,通过文献计量工具CiteSpace对Web of Science核心数据库中2011—2021 年的人工智能相关文献从合作网络、文献共被引、关键词三个角度进行可视化计量分析。研究发现:人工智能方向期刊高产国家主要集中于中国、美国、韩国,各机构、学者合作较为紧密;研究热点主要集中在深度学习、神经网络、支持向量机的理论方法及医学等智能仿真技术方向的应用;近十年人工智能方向的研究经历了蓬勃发展期、稳定期、新一轮繁荣期三个时期。 |
关键词: 人工智能;CiteSpace;可视化分析;深度学习 |
中图分类号: TP18
文献标识码: A
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Research Hotspots and Trend Analysis of International Artificial Intelligence based on CiteSpace |
SHENG Yunmeng, LIU Qian
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(School of Management, Shanghai University of Engineering and Technology, Shanghai 201620, China )
shengym2562@163.com; lqsn1996@163.com
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Abstract: In order to deeply analyze the research status and cutting-edge trends of international AI (Artificial Intelligence), and accurately understand the development stages and characteristics of AI research all over the world, this paper proposes to use CiteSpace to conduct a visual quantitative analysis of AI-related literature in the core database of Web of Science from 2011 to 2021 from three aspects: cooperative network, co-citation of literature and keywords. It is found that the high-yield countries of AI-oriented journals are mainly concentrated in China, the United States and Republic of Korea, and various institutions and scholars cooperate with each other closely. Research hotspots mainly focus on the theoretical methods of deep learning, neural networks, support vector machines and the application of intelligent simulation technologies such as medicine. Over the past decade, the research of AI has experienced three periods: vigorous development period, stable period and a new round of prosperity period. |
Keywords: artificial intelligence; CiteSpace; visual analysis; deep learning |