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Evaluation and analysis of human resource management mode and its talent screening factors based on decision tree algorithm

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Abstract

Human resource management is the cornerstone of enterprise success. In the process of enterprise management and control, the design of human resource management mode is a very important part of its management. Data mining technology provides a valuable and meaningful knowledge of extracting and mining big data. And such a technology will be an advantageous tool for human resource experts in the face of difficult and unknown talent screening. In the past, talent screening relied on many factors, such as experience, knowledge, performance and judgment ability. The screening criteria are no longer sufficient, because in this knowledge economy and business environment, the factors that facilitate someone to sit in a certain position today may not apply the next day, but in talent management, the definition of output is ensured that the right people are in the right jobs. Based on the above factors, how to select talents in the field of talent management and predict the possible future development of talents has become a challenge and problem for every organization. In this research, this research proposed data mining method with the decision tree technology to analyze data and find out the key factors that affect the on-the-job time through mining data. The results show that extended the application of data mining to the field of human resource management. Through the decision tree technology, this research contributions are companies can improve their recruitment methods and pay more attention to job seekers in the location. The policy of employee retention and employee recruitment will be improved. The key factors that affect the in-service time are predicted, and some key information that may affect the in-service time is obtained. This will help the company make correct decisions and effectively reduce the cost of company operations. This will help the company make correct decisions and effectively reduce the cost of company operations.

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  1. Logistics Department, Guangzhou Panyu Polytechnic, Guangzhou, 511483, China

    Chuanzhu Zhang

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  1. Chuanzhu Zhang
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Correspondence to Chuanzhu Zhang.

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Zhang, C. Evaluation and analysis of human resource management mode and its talent screening factors based on decision tree algorithm. J Supercomput 78, 15681–15713 (2022). https://doi.org/10.1007/s11227-022-04499-z

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  • DOI: https://doi.org/10.1007/s11227-022-04499-z

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