孙心怡,梁洪振,刘桂锋.基于文本挖掘的颠覆性技术识别方法综述[J].情报工程,2024,10(3):077-087 |
基于文本挖掘的颠覆性技术识别方法综述 |
A Review of Research on Identification of Disruptive Technologies Based on Text Mining |
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DOI:10.3772/j.issn.2095-915X.2024.03.006 |
中文关键词: 颠覆性技术;技术识别;文本挖掘;技术范式创新;突破性技术 |
英文关键词: Disruptive Technologies; Technology Identification; Text Mining; Technological Paradigm Innovation; Breakthrough Technologies |
基金项目:国家社科基金一般项目“科学数据融合模式设计与体系建构研究”(21BTQ080);江苏省教育科学规划课题高校重点项目“数智化背景下江苏省高校纪检监察工作运行模式研究”(B/2023/01/194)。 |
作者 | 单位 | 孙心怡 | 江苏大学科技信息研究所 镇江 212013 | 梁洪振 | 江苏大学科技信息研究所 镇江 212013 | 刘桂锋 | 江苏大学科技信息研究所 镇江 212013 |
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中文摘要: |
[目的/意义]对颠覆性技术的基础理论与识别方法进行梳理归纳有助于把握技术发展态势,推动数智时代面向科技创新的智能化情报服务体系构建。[方法/过程]明确颠覆性技术与文本挖掘方法的基础内涵,通过对该研究领域强关联的核心论文进行定性解读,将基于文本挖掘的颠覆性技术识别方法进行分类比较与组合分析。[局限]当前颠覆性技术识别领域应用的文本挖掘技术尚不成熟,需要进一步改进并与其他方法结合使用来优化识别效果。[结果/结论]基于文本挖掘的颠覆性技术识别方法包括突变词检测、术语词分析、共词分析、文本聚类、主题模型、语义分析。文本挖掘侧重从技术属性角度识别颠覆性技术,深度挖掘科技文本数据隐藏的潜在技术主题。 |
英文摘要: |
[Objective/Significance] The summarization of basic theories and identification methods of disruptive technologies can help grasp the technology development trend and promote the construction of intelligent intelligence service system towards scientific and technological innovation in the era of digital intelligence. [Methods/Processes] This paper firstly clarifies the connotation of disruptive technology and its related concepts, secondly introduces the concept of text mining method and the difference and connection with bibliometrics, and finally summarizes the identification methods of disruptive technologies based on text mining and carries out comparative analysis. [Limitations] Current text mining techniques applied in the field of disruptive technologies recognition are immature and need to be further improved and used in combination with other methods to optimise recognition. [Results/Conclusions] The identification methods of disruptive technologies based on text mining include mutation word detection, terminology word analysis, co-word analysis, text clustering, topic modelling, and semantic analysis. Text mining focuses on identifying disruptive technologies from the perspective of technical attributes, and deeply explores the potential technical themes hidden in scientific and technological text data. |
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