知识图谱的可视化文献计量分析

doi:10.11896/jsjkx.230500123

摘要/Abstract

摘要： 随着网络社会不断发展,人们对信息检索提出了更高要求,知识图谱的产生和发展为其提供支持。因此知识图谱研究逐渐受到学者关注,与各领域融合的相关研究也逐渐增加。为洞察知识图谱研究历程及发展趋势,文中使用CiteSpace软件,对中国知网(CNKI)和 Web of Science(WOS)数据库中知识图谱的研究进行可视化分析,按年发文量、机构共现、作者共现、关键词共现、关键词聚类及突显词对2013－2022年的文献进行梳理。文中选取中文研究中的深度学习、人工智能、文献计量、可视化,外文研究中的社会网络分析、任务分析、数据采掘、多智能体系统为研究热点进行关键词综述。通过研究发现,现阶段知识图谱相关研究尽管呈现全面深入发展趋势,但中文研究中存在联系性不强、稳定性较弱、研究范围较窄的情况,可在后续研究中进行相应完善。

关键词: 知识图谱, CiteSpace, 可视化分析, 研究热点, 研究前沿

Abstract: With the continuous development of the network society,people put forward higher requirements for information retrieval,and the emergence and development of knowledge graph provide support for it.Therefore,the research on knowledge graph has gradually attracted the attention of scholars,and the relevant research on its integration with various fields has also gradually increased.In order to gain insight into the research process and future development trend of knowledge graph,this paper uses CiteSpace software to visually analyze the research of knowledge graph in CNKI and Web of Science(WOS) databases,and sort out the documents from 2013 to 2022 according to the number of documents issued annually,institution co-occurrence,author co-occurrence,key word co-occurrence,keyword clustering and burst words.The in-depth learning,artificial intelligence,literature metrology and visualization in Chinese research,and social network analysis,task analysis,data mining,and multi-agent system in foreign language research are selected as the research hotspots for keyword review.The study finds that at this stage,despite the trend of comprehensive and in-depth development of knowledge graph related research,the Chinese research presents a weak linkage,weak stability,and a narrow research scope,which can be continuously improved accordingly in the subsequent research.

Key words: Knowledge graph, CiteSpace, Visual analysis, Research hotspot, Research frontier

中图分类号:

G206

何静, 赵睿, 张恒硕. 知识图谱的可视化文献计量分析[J]. 计算机科学, 2024, 51(6A): 230500123-10. https://doi.org/10.11896/jsjkx.230500123

HE Jing, ZHAO Rui, ZHANG Hengshuo. Visual Bibliometric Analysis of Knowledge Graph[J]. Computer Science, 2024, 51(6A): 230500123-10. https://doi.org/10.11896/jsjkx.230500123

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