规模化的历史见解:对早期现代天文表的全套机器学习分析
Oliver Eberle1,2, Jochen Büttner2,3, Hassan El-Hajj2,4
1Machine Learning Group, Technische Universität Berlin, Marchstr. 23, 10587 Berlin, Germany.
Science advances
|October 23, 2024
概括
这项研究使用人工智能分析早期现代天文学教科书,揭示了知识如何在欧洲传播,并通过机构竞争塑造了一个统一的数学文化.
科学领域:
- 科学的历史科学的历史.
- 数字人文学科 数字人文学科
- 计算社会科学 计算社会科学
背景情况:
- 分析历史知识的演变是具有挑战性的,因为大量的材料和有限的专家.
- 数字化档案为人工智能辅助的历史分析提供了新的途径.
研究的目的:
- 开发和应用人工智能驱动的方法来分析历史知识的转变.
- 揭示天文知识传播中的时间和地理模式.
主要方法:
- 使用无监督机器学习的原子化-重组方法.
- 应用可解释的人工智能技术用于历史数据分析.
- 专注于萨克罗博斯科收藏 (359版,76000页,1472年至1650年).
主要成果:
- 在天文学教科书中识别了知识转换的时间和地理模式.
- 证明了天文学教科书在培养统一数学文化的作用.
- 强调教育竞争和市场动态对知识传播的影响.
结论:
- 人工智能驱动的历史分析为知识演变提供了新的见解.
- 天文学教科书在欧洲统一数学理解方面发挥了关键作用.
- 这种方法将计算方法与传统的历史研究相结合.
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