Application of Machine Learning in Employee Recruitment: A Big Data-Driven Approach to Candidate Sourcing and Matching

The search and matching of candidates constitutes the core link of an enterprise's recruitment process. In human resource management, recruitment is a crucial step for enterprises to attract outstanding talent, directly affecting the companys future development. This review aims to conduct a comprehensive review and synthesis of the application methodologies, challenges, and development prospects of machine learning in employee recruitment within the era of big data. Research has found that in the digital age, the transformation of the recruitment process in enterprises is an inevitable trend. Machine learning is capable of precisely extracting crucial information from a vast number of resumes. It can promptly adapt to the evolving requirements of enterprises, automatically align with market trends, and rapidly identify highly-matched candidates for enterprises, thereby significantly streamlining the candidate search process. During this process, enterprises should seize the opportunities presented by technological development and propose corresponding solutions to address the associated risks and challenges. Furthermore, this review summarizes and discusses the future development prospects in the domain of employee recruitment, providing practical references for enterprises and human resources departments.