基于CiteSpace的多源数据融合研究进展

doi:10.16088/j.issn.1001-6600.2023101702

Abstract

Abstract: 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.

Key words: multi-source data fusion, knowledge graphs, CiteSpace, visual analysis, research hotspot

CLC Number: TP391

HE Jing, FENG Yuanliu, SHAO Jingwen. Research Progress on Multi-source Data Fusion Based on CiteSpace[J].Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(5): 13-27.

References

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Research Progress on Multi-source Data Fusion Based on CiteSpace

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