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High-Quality Extraction Method of Education Resources Based on Block Chain Trusted Big Data

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e-Learning, e-Education, and Online Training (eLEOT 2020)

Abstract

In order to improve the level of educational administration, it is necessary to extract educational resources with high quality Based on the block chain trust, a high-quality education resource extraction method is proposed, and a model function of high-quality education resource extraction is designed by using the spatial distribution resource scheduling model. In order to judge the convergence of high-quality education resource extraction process, a statistical analysis model of high-quality education resource extraction is established. The method of quantitative feature analysis and fuzzy information clustering is used to extract and control the high quality of educational resources. The root game equilibrium optimization algorithm realizes the optimization of the high quality of educational resources. The simulation results show that the optimization ability of using this method to extract the high quality of educational resources is better, and the scheduling process has strong convergence, it improves the ability of optimal scheduling and acquisition of educational resources.

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Correspondence to Hao Zhang .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhang, H., Zhao, B., Ma, Js. (2020). High-Quality Extraction Method of Education Resources Based on Block Chain Trusted Big Data. In: Liu, S., Sun, G., Fu, W. (eds) e-Learning, e-Education, and Online Training. eLEOT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 340. Springer, Cham. https://doi.org/10.1007/978-3-030-63955-6_8

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  • DOI: https://doi.org/10.1007/978-3-030-63955-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63954-9

  • Online ISBN: 978-3-030-63955-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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