通过自然语言处理在公共研发中的公共价值观
Hyejin Jang1,2, Taeyeon Roh1, Byungun Yoon3
1Department of Industrial & Systems Engineering, School of Engineering, Dongguk University, 3-26, Pil-dong 3-ga, Chung-gu, Seoul, 100-715, South Korea.
Scientific reports
|October 28, 2025
概括
韩国 韩国 韩国 韩国
科学领域:
- 人工智能研发政策 人工智能研发政策
- 社会影响评估的社会影响评估
- 公共价值评估 公共价值评估
背景情况:
- 韩国面临研发预算削减,需要有效的政策管理.
- 现有的研发评估方法缺乏对质量和社会影响的系统评估.
- 需要数据驱动的方法来评估公共研发超出产出指标.
研究的目的:
- 通过使用公共价值 (PV) 来评估公共研发成果的社会价值,引入一个新的框架.
- 使用自然语言处理 (NLP) 和深度学习,将研发成果与外部数据集成.
- 系统地捕捉和解释公共研发对新兴技术的社会和经济影响.
主要方法:
- 利用NLP进行专利文件解析,将其分成子节.
- 使用大型语言模型 (LLM) 分类器将分段分类为预定义的公共价值类型.
- 整合了来自公共资助的AI研发项目的1642项专利,并为社会视角提供了422篇新闻专.
主要成果:
- 在六个类别中提取了公共价值元素:工业进步,安全社会,可持续环境,创造就业机会,人类健康和生活便利.
- 分析了基于专利数量的前五个人工智能研发项目.
- 展示了一种新的,数据驱动的研发政策评估方法,使用集成数据源和先进的NLP/LLM.
结论:
- 该研究提出了一个系统的,数据驱动的框架,用于评估公共研发的社会影响.
- 调查结果为研发政策的优先级和资源分配提供了基于证据的见解.
- 这种方法通过启用以影响为导向的评估系统来推进研发政策管理.
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