信息的爆炸式增长给多源数据融合研究提供了现实基础，使其在纳入数据范围与应用前景上不断拓展，而人工智能相关技术的发展更为其提供了创新的可能。为梳理多源数据融合研究的历史脉络、发展现状与前沿趋势，本文使用CiteSpace软件，面向中国知网和Web of Science(WOS)数据库中的相关研究，按年发文量、机构共现、作者共现、关键词共现、关键词聚类与突显词，对1992-2022年的文献进行可视化分析。结果表明，近年该主题下的中外研究逐渐走向成熟，在跨学科领域的概念统一和集成方法方面日渐拓展，进入大发展期。中文研究机构和作者网络相对松散，热点研究内容相对聚焦，集中在以数据融合为核心的信息融合、多源异构数据等方面，具有注重交叉性融合、算法优化、跨领域应用等特点。外文研究机构和作者网络相对成熟和稳定，热点研究内容更加广泛，包含多源信息融合、激光雷达数据等方面，具有注重异构整合、深度洞见等特点。未来，相关研究将伴随人工智能技术发展，深入更为多元的高级算法设计和特定场景应用。研究结果可帮助研究人员展开选题和前沿识别，助力研究质量提升与创新发展。
Research Progress on Multi-source Data Fusion Based on CiteSpace
The explosive growth of information provides a realistic foundation for the study of multi-source data fusion,continuously expanding its scope of data incorporation and application prospects.The advancement of artificial intelligence technologies further offers innovative possibilities.To sort out the historical context,current status,and frontier trends of multi-source data fusion research,this paper utilizes CiteSpace software to conduct a visual analysis of relevant studies in the CNKI and Web of Science(WOS)databases,focusing on publication volume by year,institutional co-occurrence,author co-occurrence,keyword co-occurrence,keyword clustering,and prominent words from 1992 to 2022.The results indicate that in recent years,research on this topic,both domestically and internationally,has progressively matured,with unification of concepts and expansion of integrated methods in interdisciplinary fields,entering a period of significant development.Chinese research institutions and author networks are relatively loose,with focused hotspots on data fusion-centric information fusion,multi-source heterogeneous data,etc.,characterized by emphasis on cross-sectoral integration,algorithm optimization,and cross-disciplinary applications.In contrast,foreign research institutions and author networks are more mature and stable,with a broader range of hotspots including multi-source information fusion,lidar data,etc.,characterized by emphasis on heterogeneous integration and deep insights.In the future,related research will evolve alongside the development of artificial intelligence technology,delving into more diverse advanced algorithm designs and specific scenario applications.The research findings can assist researchers in topic selection and frontier identification,contributing to the improvement of research quality and innovative development.
multi-source data fusionknowledge graphsCiteSpacevisual analysisresearch hotspot
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