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The Strategy of Constructing an Interdisciplinary Knowledge Center

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019)

Abstract

This paper aims to explain the construction strategy of interdisciplinary knowledge centers from the perspective of expert systems, knowledge management and educational information technology. The method is: Firstly, it explores how to construct the strategy of interdisciplinary knowledge centers sharing, and then makes necessary explorations from computer assisted knowledge management, expert knowledge acquisition and educational autonomous learning. Finally, establish the foundation of natural language understanding in the domain knowledge base which is the basis of the interdisciplinary knowledge center. It is characterized by the application of the wisdom system studied strategy, with machine translation, machine learning and human-computer interaction, starting from the excellent courses in research universities, with the combination of intelligent text analysis and knowledge module finishing, and with the application of “seven-stapes pass” and “eight-persons group” as the education management innovation paradigm. The result is the new paradigm with both standardization and individuality, namely the construction of an interdisciplinary knowledge center that combines large production with small production. The significance lies in the combination of “language, knowledge, software, hardware formal system engineering” and “education, management, learning, application social system engineering”, that help to promote the interdisciplinary knowledge center and its systems engineering talents training. It is more efficient to build the smart systems studied for serving the society.

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Correspondence to Xiaoqun Wang .

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Zou, X., Zou, S., Wang, X. (2020). The Strategy of Constructing an Interdisciplinary Knowledge Center. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_112

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