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

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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.

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Funding

2019 Hebei Province Talent Training Project Funding Project: Research on the Construction of Highlevel Professionals with Chinese Characteristics in Higher Vocational Schools under the Integrated Development of Beijing-Tianjin-Hebei—Taking the Tourism Department of Qinhuangdao Vocational and Technical College as an example (A201901105).

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  1. Qinhuangdao Vocational and Technical College, Qinhuangdao, 066100, China

    Yuan Gao & Ximu Yan

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  1. Yuan Gao
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  2. Ximu Yan
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Correspondence to Ximu Yan.

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Gao, Y., Yan, X. Data analysis framework of tourism enterprise human resource management system based on MySQL and fuzzy clustering. Int J Syst Assur Eng Manag 14, 1647–1659 (2023). https://doi.org/10.1007/s13198-023-01969-2

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  • DOI: https://doi.org/10.1007/s13198-023-01969-2

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