Abstract
The paper takes Derwent Innovations Index (DII) patent database as the data source and analyzes the technology diffusion rules in the AI field based on the patent citation network. First, the distribution of technical force in the AI field is explored through patent quantity and patent quality. Secondly, the technological diffusion of institutions is classified based on the patent citation network. Finally, the capability of technology diffusion of institutions in the AI field is evaluated from two indicators, TDB and TDI. In the matrix diagram constructed by patent quantity and patent quality, technical force of each institution varies greatly. There are fewer institutions with high patent quantity or high patent quality, and most of the institutions still need to further improve their technical strength. In the technology diffusion network, there are three types of institutions according to the citation relationship: technology-output, technology-input and technology-comprehensive. However, it is found that the two indicators of TDB and TDI of most institutions are relatively low.
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Rongying, Z., Xinlai, L., Danyang, L. (2020). Research of Institutional Technology Diffusion Rules Based on Patent Citation Network—A Case Study of AI Field. In: Zhang, YD., Mandal, J., So-In, C., Thakur, N. (eds) Smart Trends in Computing and Communications. Smart Innovation, Systems and Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-15-0077-0_5
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DOI: https://doi.org/10.1007/978-981-15-0077-0_5
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