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Horizontal Model of Higher Education Management Policy Support System Based on Data Mining

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1283))

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Abstract

This paper expounds the concept of data mining in theory, demonstrates the core application of data mining in education management decision support system, introduces in detail the data collection, preprocessing, the establishment and maintenance of data warehouse, the selection of data mining algorithm, the specific content of decision tree algorithm, VB This paper discusses the theoretical framework of the system model, studies the great role of the combination of data mining and education management, and finally looks forward to the application prospect of data mining technology in education management decision support system.

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References

  1. Han, J.W., Kamber, M., Ming, F., Xiaofeng, M., et al.: Concepts and techniques of data mining, (trans.). Beijing Machine Press

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Author information

Authors and Affiliations

  1. Wuhan University of Technology, Wuhan, 430070, Hubei, China

    Jin Chen

Authors
  1. Jin Chen
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Corresponding author

Correspondence to Jin Chen .

Editor information

Editors and Affiliations

  1. David Goldman Informatics Centre, University of Sunderland, Sunderland, UK

    John MacIntyre

  2. University of Shanghai for Science and Technology, Shanghai, China

    Jinghua Zhao

  3. Shenzhen University, Shenzen, Guangdong, China

    Xiaomeng Ma

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

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Chen, J. (2021). Horizontal Model of Higher Education Management Policy Support System Based on Data Mining. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1283. Springer, Cham. https://doi.org/10.1007/978-3-030-62746-1_132

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