摘要
随着新一轮科技革命和产业变革的加速演进,新兴技术识别成为影响一个国家和地区未来发展战略的重要议题。本文基于德温特专利数据,引入复杂网络链路预测方法与神经网络算法构建动态预测新兴技术发展网络的方法体系,并围绕新颖性与影响力两个维度识别新兴技术主题。同时,应用钙钛矿材料领域相关数据进行实证分析,验证了本文新兴技术主题识别方法的可行性与有效性。
The acceleration of the new generation of technological revolution and industrial transformation stimulates the recognition of emerging technologies,which has become a crucial issue related to the future developmental strategy of a country and region.We initially predict the dynamic change of a co-word network based on link prediction and neural network algorithms.Emerging topics are then detected by measuring their novelty and influence.An empirical study on applications of perovskite materials is conducted to demonstrate the reliability of the proposed method.
作者
黄璐
朱一鹤
张嶷
Huang Lu;Zhu Yihe;Zhang Yi(School of Management and Economics,Beijing Institute of Technology,Beijing 100081;Centre for Artificial Intelligence,Faculty of Engineering and Information Technology,University of Technology,Sydney 2007)
出处
《情报学报》
CSSCI
CSCD
北大核心
2019年第4期335-341,共7页
Journal of the China Society for Scientific and Technical Information
基金
国家自然科学基金面上项目"基于复杂网络的全球创新研发主体组合识别与评估方法研究"(71774013)
关键词
新兴技术主题
链路预测
机器学习
加权网络
emerging topics
link prediction
machine learning
weighted networks