| 融合文献知识聚类和复杂网络的关键技术识别方法研究 |
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| 引用本文： | 王燕鹏,韩涛,陈芳.融合文献知识聚类和复杂网络的关键技术识别方法研究[J].图书情报工作,2020,64(16):105-113. |
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| 作者姓名： | 王燕鹏 韩涛 陈芳 |
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| 作者单位： | 1.中国科学院文献情报中心 北京 100190;2.中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190 |
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| 基金项目： | 本文系中国科学院文献情报中心青年人才领域前沿项目（项目编号：2019QNGR003）研究成果之一。 |
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| 摘 要： | 目的/意义] 立足情报研究视角，提出一套科学有效且可复用推广的关键技术识别方法，以期为国家、地区、企业和创新机构发现、部署、推动关键技术研发前瞻性布局提供情报支撑。方法/过程] 在关键技术类型及概念界定的基础上，利用文献知识聚类识别热点技术，以各项热点技术为节点构建复杂网络，通过节点二次聚类和可视化方法展现技术结构网络，采用结构洞理论分析网络和节点特性，以此遴选共性技术；利用链路预测方法，预测技术结构网络中的缺失边产生连接的可能性，分析热点技术交叉融合促进创新技术形成的现象，以此识别潜在新兴技术。结果/结论] 以智能制造领域为例开展关键技术识别的实证研究，通过国家权威规划文件对比和文献资料调研，初步验证方法的可操作性和有效性。
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| 关 键 词： | 关键技术识别 复杂网络 结构洞 链路预测 技术结构 |
| 收稿时间： | 2019-12-06 |
| 修稿时间： | 2020-03-29 |
Identification of Key Technologies Based on Literature Knowledge Clustering and Complex Network |
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| Wang Yanpeng,Han Tao,Chen Fang.Identification of Key Technologies Based on Literature Knowledge Clustering and Complex Network[J].Library and Information Service,2020,64(16):105-113. |
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| Authors: | Wang Yanpeng Han Tao Chen Fang |
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| Institution: | 1.National Science Library, Chinese Academy of Sciences, Beijing 100190;2.Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academic of Sciences, Beijing 100190 |
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| Abstract: | Purpose/significance] This paper try to propose a scientific, effective and reusable method to identify key technologies based on the perspective of intelligence research. It aims to provide information support for nation, regions, enterprises and innovative institutions to discover, deploy and promote the prospective R&D of key technologies.Method/process] Based on the definition of key technology and its types, this paper used K-means++ algorithm to cluster scientific papers to identify hotspot technologies. Then it used the hotspot technologies as nodes to construct and visualize complex network through secondary clustering and Gephi. Structural holes theory was adopted to analysis the network and attributes of nodes, and thereby selected generic technologies. Link prediction algorithm was used to predict the missing edges in the network according to the structure, and we can identify the potential emerging technologies based on the phenomenon of cross-fusion of hot technologies to promote the formation of innovative technologies.Result/conclusion] Taking the Intelligent Manufacturing as an example to carry out empirical research on the method, and validated the operability and effectiveness of the method through national authoritative documents and literature research. |
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| Keywords: | key technology identification complex network structural holes link prediction technical structure |
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