Abstract—The recruitment process at various organizations can be difficult, especially when there are large numbers of applicants. for less job opportunities. In this regard, the enrollment policy system has emerged as an effective tool for pre-selection appropriate space. This article focuses on the admissions policy system designed to screen students for a particular company based on their skills, where they live and their salary expectations. This system uses different algorithms to predict the quality Applicants for a particular position and shortlisted candidates are based on pre-determined criteria. The paper discusses the benefits and limitations of the input forecasting system and present some case studies where the system is available successfully implemented. The results show that the system is efficient, clear and accurate, making it more efficient. and reducing stigma in the recruitment process. Overall, this article provides insight into the power of integration policy measures to change the recruitment process in organizations and improve the quality of candidate selection.
Keywords— Machine Learning, Beautiful soup, KNN, Flask API
|
DOI:
10.17148/IJARCCE.2023.12626
