用知识图谱分析中国机器学习研究现状与趋势
Advances in Machine Learning Research Using Knowledge Graphs
- 基于CNKI数据构建机构合作与关键词共现图谱
- 揭示国内机器学习研究热点及发展脉络
- 适合关注中文AI研究动态的学者参考
本研究以中国知网（CNKI）收录的CSSCI来源文献为数据源，利用CiteSpace可视化软件绘制机构合作与关键词共现等知识图谱，系统分析中国机器学习领域的研究现状与发展态势。研究识别出当前主要研究热点与新兴趋势，同时梳理该领域面临的关键挑战，并提出针对性建议，可为后续研究提供有价值的参考。
原文摘要 · Abstract (English)
The study uses CSSCI-indexed literature from the China National Knowledge Infrastructure (CNKI) database as the data source. It utilizes the CiteSpace visualization software to draw knowledge graphs on aspects such as institutional collaboration and keyword co-occurrence. This analysis provides insights into the current state of research and emerging trends in the field of machine learning in China. Additionally, it identifies the challenges faced in the field of machine learning research and offers suggestions that could serve as valuable references for future research.
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