知识从科学流向人工智能技术:确定核心和经纪技术角色.
Seokhui Lee1, Jisoo Hur2, Junseok Hwang1
1Technology Management, Economics and Policy Program, College of Engineering/ Integrated Major in Smart City Global Convergence, Seoul National University, Seoul, Republic of Korea.
PloS one
|February 19, 2026
概括
这项研究绘制了人工智能 (AI) 中从科学到技术的知识流. 我们分析了人工智能专利,揭示了关键趋势和创新途径,为研发和政策提供了洞察力.
科学领域:
- 人工智能 (AI) 是一种人工智能.
- 创新研究 研究 创新研究
- 图书统计学 图书统计学
背景情况:
- 人工智能 (AI) 正在快速发展和跨行业整合.
- 从科学研究到人工智能技术开发的知识流动至关重要,但研究不足.
- 现有的研究缺乏对AI的科学技术知识途径的系统分析.
研究的目的:
- 系统地调查支人工智能的发展的科学到技术知识流.
- 提出和应用一个语义框架来探索与人工智能相关的知识转移.
- 确定人工智能发展中的关键技术趋势和结构性途径.
主要方法:
- 开发了一个两阶段的框架:技术分类和语义主题探索.
- 机密AI专利使用CPC共发生网络的中心性措施.
- 应用BERTopic对专利和科学出版物摘要的建模,使用生成AI进行主题标签.
主要成果:
- 分析了2002年至2021年期间提交的AI专利.
- 追踪了关键的技术趋势,并确定了知识流的结构性途径.
- 揭示了科学发现和人工智能创新之间的动态相互作用.
结论:
- 这些发现提供了对人工智能的技术演变的结构性理解,这是由科学知识驱动的.
- 为企业的研发 (R&D) 战略提供实用意义.
- 为快速发展的人工智能领域的创新政策设计提供信息.
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