信息资源管理学报 ›› 2024, Vol. 14 ›› Issue (4): 103-116.doi: 10.13365/j.jirm.2024.04.103

• 研究论文 • 上一篇    下一篇

高校高价值专利技术机会识别研究——以“生成式人工智能”领域为例

冉从敬 李旺 黄文俊   

  1. 武汉大学信息管理学院,武汉,430072
  • 出版日期:2024-07-26 发布日期:2024-08-14
  • 作者简介:冉从敬,教授,博士,博士生导师,研究方向为知识产权、大数据治理;李旺(通讯作者),博士研究生,研究方向为数据科学、知识产权,Email:15147149291@163.com;黄文俊,硕士研究生,研究方向为知识产权、数据主权。
  • 基金资助:
    本文系国家社会科学基金青年项目“基于知识元的高校专利质量智能判别及其推荐研究”(23CTQ028);国家自然科学面上项目“基于图卷积神经网络的新兴技术领域高质量专利识别及其演化研究”(72274084);山东省自然科学基金青年项目“基于专利计量与机器学习的校企技术合作供需智能匹配方法研究”(ZR2023QG105)的研究成果之一。

Identifying Technology Opportunities from High-Value Patents in Universities: The Case of Generative Artificial Intelligence

Ran Congjing Li Wang Huang Wenjun   

  1. School of Information Management, Wuhan University, Wuhan, 430072
  • Online:2024-07-26 Published:2024-08-14
  • About author:Ran Congjing, professor, Ph.D., doctoral supervisor, research interests: intellectual property, big data governance; Li Wang (corresponding author), Ph.D. candidate, research interests: data science, intellectual property, Email: 15147149291@163.com; Huang Wenjun, M.S. candidate, research interests: intellectual property, data sovereignty.
  • Supported by:
    This work is supported by the National Social Science Foundation of China Youth Program "Intelligent Judgment of Patent Quality in Universities Based on Knowledge Element and its Recommendation Research"(23CTQ028);the National Natural Science Program of China, "Identification of High Quality Patents in Emerging Technologies Based on Graph Convolutional Neural Networks and Its Evolutionary Study"(72274084) and the Shandong Province Natural Science Foundation Youth Project "Research on Intelligent Matching Method of Supply and Demand for University-Enterprise Technology Cooperation Based on Patent Measurement and Machine Learning"(ZR2023QG105).

摘要: 提出一种高校高价值专利技术机会识别方法,使用主题建模、突变级数法、机器学习与离群值检测算法,在评估出高校高价值专利的基础上,进一步识别出具有潜在技术机会的技术主题与专利技术。以“生成式人工智能”领域为例进行实证,研究结果表明:“生成式人工智能”领域的潜在技术主题集中在深度学习、神经网络与机器学习等前沿领域,AI影像、AI诊疗等技术为该领域的潜在技术机会,且上述技术均有国家相关政策大力支撑。本研究方法突破了单一技术机会识别方法识别结果针对性不强、识别专利价值不大、识别结果形式较为单一等核心问题,相关识别结果可以为高校技术转移、技术研发与技术创新提供决策支撑。

关键词: 高价值专利, 专利价值评估, 技术机会识别, 突变级数法, 离群值检测算法

Abstract: This study proposes a method for identifying technological opportunities of high-value patents in colleges and universities, using theme modeling, mutation level method, machine learning and outlier detection algorithms to further identify technological themes and patented technologies with potential technological opportunities on the basis of evaluating high-value patents in colleges and universities. Taking the field of "Generative Artificial Intelligence" as an example for empirical evidence, the results show that the potential technology themes in the field of "Generative Artificial Intelligence" are centered on cutting-edge areas such as deep learning, neural networks and machine learning, and AI imaging and AI diagnosis and treatment are potential technological opportunities in this field, and the above technologies are vigorously supported by relevant national policies. This method can break through the core problems such as poor targeting of the identification results of a single technology opportunity identification method, low value of the identified patents, and a single form of the identification results, and the relevant identification results can provide decision-making support for the technology transfer, technology research and development, and technological innovation of universities.

Key words: High-value patents, Patent valuation, Technology opportunity identification, Catastrophe progression method, Local outlier factor

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