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Enterprise Strategic Financing Risk Management Auxiliary Education System Based on Data Mining

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e-Learning, e-Education, and Online Training (eLEOT 2022)

Abstract

In order to ensure the use effect of enterprise strategic financing risk management auxiliary education system, an enterprise strategic financing risk management auxiliary education system based on data mining is designed. By designing the system hardware structure, combined with data mining algorithm, optimize the functional structure of the system software, simplify the auxiliary education process of enterprise strategic financing risk management, and realize the auxiliary education of enterprise strategic financing risk management. Through the analysis of the system test results, it can be seen that the enterprise strategic financing risk management auxiliary education system based on data mining has high practicability and fully meets the user experience in the process of practical application.

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Funding

Fund Project
  1. 1.

    “Qinglan Project” of Jiangsu Universities - Training Project for Outstanding Young Backbone Teachers (RS21QL01).

  2. 2.

    “Excellent Project of Social Science Application Research in Jiangsu Province” - Special Project of Collaborative Innovation Base (22XTB-77).

  3. 3.

    Key Project of the “14th Five-Year Plan” for Educational Science in Jiangsu Province (B/2022/02/44).

  4. 4.

    Provincial and Ministerial Subject Cultivation Project of Wuxi Vocational Institute of Commerce (KJXJ21602).

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Correspondence to Xiang Zou .

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zou, X., Zhu, J. (2022). Enterprise Strategic Financing Risk Management Auxiliary Education System Based on Data Mining. In: Fu, W., Sun, G. (eds) e-Learning, e-Education, and Online Training. eLEOT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 453. Springer, Cham. https://doi.org/10.1007/978-3-031-21161-4_7

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  • DOI: https://doi.org/10.1007/978-3-031-21161-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21160-7

  • Online ISBN: 978-3-031-21161-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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