探索生物研究热点通过一种新的图书识别方法
Shan Chen1, Junsha Wang2, Xinyu Huang3
1Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore City 637616, Singapore.
Computational biology and chemistry
|September 13, 2025
概括
这项研究引入了一种使用R绘制生物学研究趋势的新型图书识别分析. 它建议整合大数据和机器学习,以获得更深入的见解和生物学的未来预测.
科学领域:
- 生物科学 生物科学
- 生命科学研究 生命科学研究
背景情况:
- 生物研究是根本性的,影响人类生活的各个方面.
- 了解研究趋势对于科学进步至关重要.
研究的目的:
- 确定当前的研究热点和生物学中的未来趋势.
- 通过使用R编程语言引入一种创新的图书识别分析方法.
- 提出未来的研究方向,整合大数据和机器学习.
主要方法:
- 使用R编程语言进行图书统计分析.
- 与VOSviewer等传统方法进行比较.
- 数据集成和机器学习模型培训.
主要成果:
- 确定关键的研究领域和生物研究的新兴趋势.
- 证明基于R的文献计量方法对深入分析的有效性.
- 验证大数据和机器学习的拟议整合.
结论:
- 基于R的文献计量方法为生物学研究趋势提供了新的视角.
- 整合大数据和机器学习对未来的生物见解和预测具有重大潜力.
- 这项研究为生命科学领域的高级文献识别分析提供了路线图.
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