将 AI 创新从学术研究映射到工业专利的全球数据集
A Global Dataset Mapping the AI Innovation from Academic Research to Industrial Patents
AI总结：
本文提出全球数据集 DeepInnovationAI，包含专利、学术论文及论文-专利对三个子集，利用大语言模型、双层 BERT 分类器和超图分析等技术识别 AI 内容并映射知识流动，为分析 AI 创新与技术转移奠定基础。
摘要：
在快速发展的人工智能（AI）领域，映射创新模式并理解从研究到应用的有效技术转移对经济增长至关重要。然而，现有数据基础设施存在碎片化、覆盖不全和评估能力不足的问题。在此，我们提出 DeepInnovationAI，一个包含三个结构化文件的综合全球数据集。DeepPatentAI.csv：包含 2,356,204 条专利记录，具有 8 个特定字段属性。DeepDiveAI.csv：包含 3,511,929 篇学术出版物，具有 13 个元数据字段。这两个数据集利用大语言模型、多语言文本分析和双层 BERT 分类器准确识别 AI 相关内容，同时利用超图分析创建稳健的创新指标。此外，DeepCosineAI.csv：通过应用语义向量邻近分析，该文件包含 3,511,929 对最相关的论文-专利对，每对由 3 个元数据字段描述，以促进潜在知识流动的识别。DeepInnovationAI 使研究人员、政策制定者和行业领袖能够预测趋势并识别合作机会。凭借广泛的时间和地理范围，它支持对技术发展模式和国际竞争动态的详细分析，为建模 AI 创新和技术转移过程奠定基础。
英文摘要：
In the rapidly evolving field of artificial intelligence (AI), mapping innovation patterns and understanding effective technology transfer from research to applications are essential for economic growth. However, existing data infrastructures suffer from fragmentation, incomplete coverage, and insufficient evaluative capacity. Here, we present DeepInnovationAI, a comprehensive global dataset containing three structured files. DeepPatentAI.csv: Contains 2,356,204 patent records with 8 field-specific attributes. DeepDiveAI.csv: Encompasses 3,511,929 academic publications with 13 metadata fields. These two datasets leverage large language models, multilingual text analysis and dual-layer BERT classifiers to accurately identify AI-related content, while utilizing hypergraph analysis to create robust innovation metrics. Additionally, DeepCosineAI.csv: By applying semantic vector proximity analysis, this file contains 3,511,929 most relevant paper-patent pairs, each described by 3 metadata fields, to facilitate the identification of potential knowledge flows. DeepInnovationAI enables researchers, policymakers, and industry leaders to anticipate trends and identify collaboration opportunities. With extensive temporal and geographical scope, it supports detailed analysis of technological development patterns and international competition dynamics, establishing a foundation for modeling AI innovation and technology transfer processes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
