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Data analysis framework of tourism enterprise human resource management system based on MySQL and fuzzy clustering

Author

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  • Yuan Gao

    (Qinhuangdao Vocational and Technical College)

  • Ximu Yan

    (Qinhuangdao Vocational and Technical College)

Abstract

The essential task of enterprise human resource management is complicated, involving many departments, so the work is difficult. By applying data analysis technology to enterprise human resource management, the way of human resource management can be expanded. The competition among enterprises is mainly the competition of enterprise talents. If the company has top talents in the industry, they can occupy a certain market share, which can ensure a good consumption market in the fierce market competition. Therefore, in the business development of enterprises, we must attach great importance to human resources management and increase investment in human resources management in combination with the actual situation. Human resource management needs to deal with a lot of information. The emergence of database and fuzzy clustering algorithm makes the development of human resource work convenient and efficient, and further improves the level of human resource management. This paper introduces the design of distributed database and fuzzy clustering algorithm based on artificial intelligence, and constructs a data analysis model of human resource management system of tourism enterprises. The performance of the designed model is demonstrated through systematic simulations under different scenarios.

Suggested Citation

  • Yuan Gao & Ximu Yan, 2023. "Data analysis framework of tourism enterprise human resource management system based on MySQL and fuzzy clustering," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1647-1659, October.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01969-2
    DOI: 10.1007/s13198-023-01969-2
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