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面向技术发展脉络分析的专利引证类时序模型及图谱研究

周莉 陈荣 严素梅 程月月

数字图书馆论坛2023,Vol.19Issue(12):44-55,12.
数字图书馆论坛2023,Vol.19Issue(12):44-55,12.DOI:10.3772/j.issn.1673-2286.2023.12.005

面向技术发展脉络分析的专利引证类时序模型及图谱研究

Patent Citation Class Time Series Model and Map for Technology Development Analysis

周莉 1陈荣 2严素梅 2程月月3

作者信息

  • 1. 华东理工大学科技信息研究所,上海 200237||上海师范大学图书馆,上海 200233
  • 2. 华东理工大学科技信息研究所,上海 200237
  • 3. 复旦大学国家智能评价与治理实验基地,上海 200433
  • 折叠

摘要

Abstract

The analysis of the technology development context is helpful to accurately grasp the direction of technological innovation and effectively identify the priority development technology field.In this study,the patents with citation relationship are used as the data source,and the calculation formula of patent citation relevance is proposed in combination with citation frequency and citation level.According to the patent citation relevance,the patents that play a core role in the process of technology development are selected as the research data set.The research data set is divided into subject domain,and time series is introduced to construct a three-dimensional class time series model of technology theme,technology field,and time series.Based on this model,a multi-dimensional patent citation knowledge map is drawn for multi-level technology development context analysis.The field of volatile organic compounds treatment technology is selected for empirical analysis,and the patent citation knowledge map of a technology in this field is constructed.The development context is analyzed from multiple dimensions.It is found that the technology is developed by the integration of the separation technology field and the acyclic or carbocyclic compound technology field,which verifies the usefulness of this research method.

关键词

类时序模型/知识图谱/专利引证分析/技术发展脉络分析/挥发性有机物

Key words

Class Time Series Model/Knowledge Map/Patent Citation Analysis/Analysis of Technology Development/Volatile Organic Compound

引用本文复制引用

周莉,陈荣,严素梅,程月月..面向技术发展脉络分析的专利引证类时序模型及图谱研究[J].数字图书馆论坛,2023,19(12):44-55,12.

基金项目

本研究得到上海市软科学研究计划项目"基于量化趋势演化模型的技术发展预见与实证研究"(编号:18692109200)资助. (编号:18692109200)

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