Abstract
Excellent employees bring considerable benefits to the company, but once they leave, they will also cause great losses to the company. Therefore, it is necessary to establish a credible evaluation system for the behavior of outstanding employees, evaluate their daily performance, and predict their probability of leaving. Based on data mining technology, this paper analyzes the resignation information of employees’ data provided by kaggle. According to Price-Muller employee separation theory and analogy with customer life cycle theory, we further excavate and analyze the reasons why employees leave. Finally, we define and evaluate the excellent employees in the enterprise.
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Wang, B. (2021). Evaluation Method of the Excellent Employee Based on Clustering Algorithm. In: Dai, HN., Liu, X., Luo, D.X., Xiao, J., Chen, X. (eds) Blockchain and Trustworthy Systems. BlockSys 2021. Communications in Computer and Information Science, vol 1490. Springer, Singapore. https://doi.org/10.1007/978-981-16-7993-3_46
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DOI: https://doi.org/10.1007/978-981-16-7993-3_46
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