情报研究

基于专利术语的颠覆性技术识别及实证研究

  • 徐硕 ,
  • 李静鸿 ,
  • 安欣
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  • 1 北京工业大学经济与管理学院 北京 100124;
    2 北京林业大学经济管理学院 北京 100083
徐硕,教授,博士,博士生导师;李静鸿,硕士研究生。

收稿日期: 2023-03-13

  修回日期: 2023-08-16

  网络出版日期: 2024-02-02

基金资助

本文系国家自然科学基金项目“科技关联视角下新兴技术弱信号扫描预判方法研究”(项目编号:72074014)研究成果之一。

Disruptive Technology Identification and Empirical Study on the Basis of Patent Terms

  • Xu Shuo ,
  • Li Jinghong ,
  • An Xin
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  • 1 School of Economics and Management, Beijing University of Technology, Beijing 100124;
    2 School of Economics and Management, Beijing Forestry University, Beijing 100083

Received date: 2023-03-13

  Revised date: 2023-08-16

  Online published: 2024-02-02

摘要

[目的/意义] 为识别及预判当前受到高度关注的颠覆性技术,以专利术语为基础构建颠覆性技术识别指标,并对太阳能光伏领域的专利进行实证研究。[方法/过程] 基于全文本内容,兼顾技术创新性和技术影响力两个维度,构建涵盖 5 个指标的颠覆性技术识别指标体系;并采用自然语言处理技术抽取专利术语,将识别问题转化为经典的二分类问题训练机器学习模型;同时针对训练样本类别分布不平衡的问题,引入决策曲线分析以确定最优的分类阈值。[结果/结论] 实证研究在太阳能光伏领域 2 196 个专利中预判出 91 个颠覆性专利,取得较好的预测效果,验证本文提出的颠覆性技术识别方法的有效性,为颠覆性技术预判、专利价值衡量等研究提供新的视角。

本文引用格式

徐硕 , 李静鸿 , 安欣 . 基于专利术语的颠覆性技术识别及实证研究[J]. 图书情报工作, 2024 , 68(2) : 62 -72 . DOI: 10.13266/j.issn.0252-3116.2024.02.006

Abstract

[Purpose/Significance] This paper builds a disruptive indicator system based on patent terminologies to identify and predict disruptive technologies, and selects relevant patents in the field of solar photovoltaics for empirical study.[Method/Process] This paper built a disruptive indicator system with 5 indicators from patent full texts by considering two dimensions of technological innovation and technological influence based on patent terminologies. The process transformed the identification problem into a classic binary classification problem through the natural language processing techniques to train a machine learning model, and introduced decision curve analysis to determine the optimal classification threshold for the problem of unbalanced samples.[Result/Conclusion] The empirical study in the field of solar photovoltaic identifies 91 disruptive patents among 2 196 patents, which gets a better predictive performance and verifies the validity of the indicators. In summary, the proposed approach provides a new perspective for future research on how to predict disruptive technologies, measure patent value, and identify promising technologies.

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