Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (12): 46-53.DOI: 10.3778/j.issn.1002-8331.2102-0315

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Research Hotspots and Cutting-Edge Mining of Artificial Intelligence

WANG Youfa, CHEN Hui, LUO Jianqiang   

  1. School of Management, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • Online:2021-06-15 Published:2021-06-10

国内外人工智能的研究热点对比与前沿挖掘

王友发,陈辉,罗建强   

  1. 江苏大学 管理学院,江苏 镇江 212013

Abstract:

In order to intuitively understand the development status and research frontier of artificial intelligence, analyze the similarities and differences between domestic and foreign research, and help domestic artificial intelligence research. Based on the journal papers from 2008 to 2019 in Web of science database and CNKI database, scientific knowledge mapping and visual analysis of journal papers are carried out with Citespace software. According to the objective data and the map of scientific knowledge, it is found that after 2016, the field of artificial intelligence ushers in a new upsurge, and presents a pattern of “China and the United States”. In terms of the quality of published papers, North America is currently the region with the highest level of artificial intelligence research. At present, the main force of artificial intelligence research is colleges and universities, and the system of combining production, teaching and research has not yet formed. The research topics have distinct characteristics of the times, and artificial neural networks, algorithms, big data, robots, computer vision, legal ethics and so on have become the current research hotspots. Finally, according to the evolution of artificial intelligence research context and high-frequency words, three research frontiers of this field, namely “deep reinforcement learning”, “artificial intelligence +” and “intelligent social science”, are put forward to provide direction suggestions for the follow-up artificial intelligence research.

Key words: artificial intelligence, knowledge graph, research hotspots, research frontier

摘要:

为了直观地了解人工智能领域发展现状及研究前沿,剖析国内外研究存在的异同点,助力国内人工智能研究。以Web of Science数据库和CNKI数据库的2008—2019年期刊论文为依据,借助Citespace软件对期刊论文进行科学知识图谱绘制和可视化分析。根据客观数据和科学知识图谱发现:2016年后,人工智能领域迎来新的研究热潮,且呈现“中美双雄”的格局;在发文质量上,北美区域是当前人工智能研究水平最高的区域;目前,人工智能研究的主力军是高校,且尚未形成产学研相结合的体系;研究主题具有鲜明的时代特征,人工神经网络、算法、大数据、机器人、计算机视觉、法律伦理学等成为当下的研究热点;最后根据人工智能研究脉络演进图与高频突现词提出该领域的“深度强化学习”“人工智能+”“智能社会科学”三个研究前沿,为后续人工智能研究提供方向建议。

关键词: 人工智能, 知识图谱, 研究热点, 研究前沿