Construction and application of intelligent human resource management system based on machine learning algorithm

Abstract

Traditional human resource management systems face the problems of low efficiency and insufficient accuracy in data processing and decision support, while intelligent human resource management systems based on machine learning algorithms can significantly improve management efficiency and decision-making accuracy through advanced data analysis and automated decision-making. By analyzing the training duration and response efficiency of various algorithms, it was observed that the machine learning algorithm’s training time is approximately 10.3 times longer than that of the non-optimized machine learning algorithm and 3.6 times longer than that of the intelligent management system, indicating strong time performance. Additionally, the response time of the classification model after applying feature selection is slightly improved compared to the original machine learning algorithm, measuring 225% of the non-optimized version and 98% of the response time of the intelligent HR management system. The key technologies involved in system development include neural network models and classification analysis techniques, and the implementation of these algorithms in the intelligent HR management system provides notable benefits.