图书情报工作

图书情报工作 >

2026 , Vol. 70 >Issue 19: 56 - 71

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.19.005

研究论文

基于“技术语义—应用场景”双重模糊消解的潜在新兴技术识别研究

  • 张新雨 ,
  • 白如江 ,
  • 牛湘荷 ,
  • 石文秀 ,
  • 刘琦 ,
  • 孔玲
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  • 山东理工大学信息管理学院 淄博 255049
张新雨，硕士研究生；白如江，教授，博士，博士生导师，通信作者，E-mail：brj@sdut.edu.cn；牛湘荷，硕士研究生；石文秀，硕士研究生；刘琦，硕士研究生；孔玲，讲师，博士。
32305.14.CN11-1541.2026.19.005

收稿日期: 2025-07-30

  修回日期: 2025-10-10

  网络出版日期: 2026-09-24

基金资助

本文系山东省社会科学规划研究青年项目“知识关联视角下绿色低碳技术知识表示与机会识别研究”（项目编号：24DTQJ02）研究成果之一。

收起

Research on Potential Emerging Technology Identification Based on Dual Fuzzy Decomposition of “Technical Semantics—Application Scenarios”

  • Zhang Xinyu ,
  • Bai Rujiang ,
  • Niu Xianghe ,
  • Shi Wenxiu ,
  • Liu Qi ,
  • Kong Ling
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  • School of Information Management, Shandong University of Technology, Zibo 255049
Zhang Xinyu, Master’s Candidate; Bai Rujiang, Professor, PhD, Doctoral Supervisor, E-mail: brj@sdut.edu.cn; Niu Xianghe, Master’s Candidate; Shi Wenxiu, Master’s Candidate; Liu Qi, Master’s Candidate; Kong Ling, Lecturer, PhD.

Received date: 2025-07-30

  Revised date: 2025-10-10

  Online published: 2026-09-24

Supported by

This work is supported by the Shandong Social Science Planning Research Youth Project titled “Research on Knowledge Representation and Opportunity Identification of Green and Low-Carbon Technology from the Perspective of Knowledge Association”(Grant No.24DTQJ02).

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摘要

[目的/意义] 潜在新兴技术因其固有的模糊性特征易使其陷入识别困境，本文旨在构建适配其模糊性特征的识别体系，实现对潜在新兴技术的有效识别，为科技创新资源配置与未来产业发展提供支撑。[方法/过程] 基于潜在新兴技术模糊性特征及其表现形式，以专利、新闻和报告为数据源，从技术语义模糊与应用场景模糊两个特征维度构建识别模型：首先，基于动态网络与模糊C均值聚类方法，构建跨领域关联强度和归属不确定性指标识别语义模糊技术；其次，借助BERTopic主题模型，构建技术应用多样性和场景跃迁指标识别应用场景模糊技术；最后，为综合技术语义模糊指标和综合应用场景模糊指标赋权，以识别最终潜在新兴技术。[结果/结论] 以氢燃料电池领域为实证对象，依据二八定律，设定综合得分前20%的分位数（即综合潜在得分≥0.32）作为识别阈值，最终识别出质子交换膜燃料电池、空气燃料电池、阴离子交换膜燃料电池、固体氧化物燃料电池、空冷燃料电池5项潜在新兴技术，并将识别结果与国家政策报告等进行验证，有效支持了本研究的有效性与可靠性。

关键词： 技术语义模糊; 应用场景模糊; 潜在新兴技术; 双重视角

本文引用格式

张新雨 , 白如江 , 牛湘荷 , 石文秀 , 刘琦 , 孔玲 . 基于“技术语义—应用场景”双重模糊消解的潜在新兴技术识别研究[J]. 图书情报工作, 2026 , 70(19) : 56 -71 . DOI: 10.13266/j.issn.0252-3116.2026.19.005

Abstract

[Purpose/Significance] Potential emerging technologies are prone to recognition difficulties due to their inherent fuzzy characteristics. This article aims to construct a recognition system that is adapted to their fuzzy characteristics, achieve effective recognition of potential emerging technologies, and provide support for the allocation of technological innovation resources and future industrial development. [Method/Process] Based on the fuzziness characteristics of potential emerging technologies and their manifestations, using patents, news, and reports as data sources, a recognition model is constructed from two feature dimensions: technical semantic fuzziness and application scenario fuzziness. Firstly, based on dynamic networks and fuzzy C-means clustering methods, cross-domain association strength and attribution uncertainty indicators are constructed to identify semantic fuzziness technology. Secondly, with the help of the BERTopic topic model, a fuzzy technology for identifying application scenarios based on technology application diversity and scenario transition indicators is constructed. Finally, assign weights are assigned to the comprehensive technical semantic ambiguity index and the comprehensive application scenario ambiguity index to identify potential emerging technologies. [Result/Conclusion] With the field of hydrogen fuel cells as the empirical object, based on the Pareto Principle, the top 20% percentile of the comprehensive score (i.e., comprehensive potential score ≥ 0.32) is set as the recognition threshold, and finally 5 potential emerging technologies are identified.

Key words： technical semantic ambiguity; fuzzy application scenarios; potential emerging technologies; dual perspective

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