Abstract
With the rapid development of artificial intelligence (AI) technology, AI not only brings important technological changes to the society, but also brings challenges for the society to cope with and develop AI. Based on the patent data published by China Intellectual Property Office (CNIPA) from 1993 to 2018, this paper studies the knowledge flow of AI: knowledge output, knowledge source and knowledge outflow by using patent forward citation and backward citation, and comprehensively evaluates the knowledge flow of AI in each year with entropy weight method. The results show that, although AI has experienced explosive growth in recent years, its knowledge flow is more and more concentrated in the United States, China, Japan and other countries, and its knowledge source and knowledge outflow depend on the knowledge with updated temporal dimension, closer geographical dimension and closer technical dimension. This research will provide valuable reference for relevant countries and enterprises to understand the changes and trends of AI patents.
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The authors received financial support from the National Natural Science Foundation of China (Grant no. 71904137) and Ministry of Education of the People’s Republic of China (Grant no. 18YJC630227).
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Zhou, W., Gu, X., Yang, X. (2021). Knowledge Flow in the Field of Artificial Intelligence: An Analysis Based on CNIPA Patents. In: Xu, J., García Márquez, F.P., Ali Hassan, M.H., Duca, G., Hajiyev, A., Altiparmak, F. (eds) Proceedings of the Fifteenth International Conference on Management Science and Engineering Management. ICMSEM 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-79203-9_46
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