Optimization of Human Resource Recruitment Efficiency Based on Machine Learning Algorithms

With the rapid development of information technology, the application of information management systems has penetrated into various aspects of enterprise operation, becoming a key factor in promoting continuous innovation and development of enterprises. In this context, human resource management has also ushered in a wave of digital transformation, among which online recruitment, as an important way to acquire talent, has received widespread attention for its efficiency and accuracy. Although online recruitment provides job seekers and recruiting units with a broader platform and convenient channels, in practical operation, it still faces many challenges such as low efficiency in personnel position matching and imbalanced matching results. How to accurately and quickly complete job matching has become an urgent problem in the field of human resources. In response to this situation, this article proposes a human resources recruitment system based on machine learning (ML) algorithm. This system integrates advanced ML technology to deeply analyze and mine massive recruitment and job search data, in order to achieve precise matching between job seekers and recruitment positions. The experimental results show that the system has achieved significant results in improving the efficiency of personnel position matching.