基于知识图谱的矿山开采沉陷研究发展分析

Development analysis of mining subsidence research based on knowledge graph

  • 摘要: 针对矿山开采沉陷知识图谱构建问题,基于中国知网和Web of Science数据库的文献资料,采用CiteSpace引文网络可视化工具进行分析,通过绘制发文数量、研究机构及关键词聚类等知识图谱,揭示矿山开采沉陷领域的研究热点和前沿趋势。研究结果表明:近年来,中国学术界高度关注开采沉陷问题,中国机构在发文数量上领先,中国矿业大学以1 456篇发文量居首位;目前国内外研究热点,集中在高精度监测技术和复杂环境下的沉陷预测及监测问题;开采沉陷机理研究、基于多源数据融合的沉陷监测数据获取、生态修复正成为开采沉陷研究的重要发展方向。

     

    Abstract: Focusing on mining subsidence research, this study conducted a comprehensive analysis using the CiteSpace citation network visualization tool based on literature from both the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) databases. By analyzing publication volume, research institutions, and keyword clusters, this study maps knowledge graphs of research institutions and keywords to uncover research hotspots and frontier trends in the field of mining-induced subsidence. The results indicate that there is a high level of attention from the academic community regarding subsidence issues; Chinese institutions dominate in terms of publication quantity, with China University of Mining and Technology leading with 1 456 papers. Currently, both domestic and international research hotspots focus on high-precision monitoring technology and subsidence prediction and monitoring in complex environments. The integration of multi-source data has become a significant trend in mining subsidence monitoring and research.

     

/

返回文章
返回