Abstract
The patent has considerable impact on innovation of technology and enhancement of competitiveness. Conventional community detection methods and text mining technologies play a crucial role in patent analysis and knowledge discovery, but evident obstacles have gradually emerged as non-parallel processing and inability of the community structure to vary with the terms. Herein, in our study we divide the knowledge network into a three-layer structure for each layer executing in parallel and model the community formation as a game process for maximizing the utility of each node adaptively. Through keywords and semantic relationships of patent knowledge, we propose a novel community detection algorithm integrating game theoretic framework.
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Sun, Y., Liu, S., Liu, W. (2021). Patent Semantic Community Detection Based on Game Theory. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_120
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DOI: https://doi.org/10.1007/978-3-030-53980-1_120
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