系统工程与电子技术

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数据驱动的技术创新网络模体分析

徐建国, 李孟军, 姜江, 游翰霖   

  1. 国防科学技术大学信息系统与管理学院, 湖南 长沙 410073
  • 出版日期:2017-04-28 发布日期:2010-01-03

Data-driven motif analysis of technology breakthrough network

XU Jianguo, LI Mengjun, JIANG Jiang, YOU Hanlin   

  1. College of Information System and Management, National University of Defense Technology, Changsha 410073, China
  • Online:2017-04-28 Published:2010-01-03

摘要:

针对现有技术体系如何实现定量化的网络化建模和识别技术创新的模式和机理两个主要问题,提出数据驱动的技术创新网络构建方法,挖掘出技术文档的关键字向量,结合向量空间模型实现技术相似度的定量计算,生成技术创新时序网络。讨论了技术创新网络基本结构,分析了技术创新网络的模体类型与特性,并计算了模体重要性剖面以进一步确定其网络特征,得出技术创新具有强合作性且技术创新网络与生物网络以及信号传输网络属于同一个网络超家族的结论。并以技术评论数据为例验证了该方法的有效性。

Abstract:

To solve the quantitative network modeling of technology network and distinguish the mode of technology breakthrough, a data-driven network modeling approach is proposed. The similarity between technologies is computed quantitatively with vector space model and the keyword vector of technology document, which aims to model the sequential network. The basic structure and motif characteristic of technology breakthrough network are discussed. The significance profile is calculated to emulate the network deeply. Experimental results of technology review data confirm the effectiveness of the proposed approach and show that there is a strong cooperation between innovational technologies and the network is similar with biological network and signal-transduction network, which all belong to the network superfamily.