文献类型：期刊文献

英文题名：Weighted node importance contribution correlation matrix for identifying China’s core metro technologies with patent network analysis

作者：Long, Mei[1]; Ma, Tieju[1]

机构：[1] Business School, East China University of Science and Technology, Shanghai, China

年份：2016

卷号：9983 LNAI

起止页码：199

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20164402972260)

语种：英文

外文关键词：Matrix algebra - Patents and inventions

摘要：The purpose of this study is to identify the core technologies in the metro domain by analyzing its patent network, which is beneficial for grasping technological trends and advancing the metro domain in China. Metro patent data (1986–2016) published in China were collected from the State Intellectual Property Office of the People’s Republic of China. Then, we built a patent network with co-occurrence of information from the International Patent Classification, and improved the node importance contribution correlation matrix method to a weighted version in order to calculate the importance of each node. Nodes with high importance scores play more crucial roles in efficiency and stability of the network, and are viewed as the core metro technologies. The results can be useful for companies’ technology R&D planning and government policymaking. ? Springer International Publishing AG 2016.