Open Access Paper
11 November 2021 Theoretical research and improvement of knowledge conversion (Withdrawal Notice)
Rongying Zhao, Zhuozhu Liu, Junling Wang, Yuxin Hu, Yiran Li
Author Affiliations +
Proceedings Volume 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence; 1207615 (2021) https://doi.org/10.1117/12.2612191
Event: Fourth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2021), 2021, Shanghai, China
Abstract
This paper reconsiders the SECI model proposed by Ikujiro Nonaka, and points out the inconformity between theory and practice in the original model when knowledge conversion is based on the theoretical basis and the actual situation, that is, socialization or combination can not be realized directly, but can only be realized indirectly through the combination of internalization and externalization. On this basis, the model is improved, and the spatial vector model of knowledge conversion is proposed. The SECI model is innovated, which provides theoretical support for the subsequent research on knowledge conversion. Through the establishment of knowledge conversion model in the spatial vector coordinate system, the specific transformation mode between explicit knowledge and tacit knowledge is embodied, and the inner conversion mode of combinatorial and socialized is refined. Through the study of knowledge conversion model, this paper holds that there are two direct ways of knowledge conversion, namely externalization and internalization.
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Rongying Zhao, Zhuozhu Liu, Junling Wang, Yuxin Hu, and Yiran Li "Theoretical research and improvement of knowledge conversion (Withdrawal Notice)", Proc. SPIE 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence, 1207615 (11 November 2021); https://doi.org/10.1117/12.2612191
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KEYWORDS
3D modeling

Knowledge management

Transform theory

Vector spaces

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