Intelligent Employer Matching System for Young Professionals and Students Based on Multifactor Analysis

Abstract

The article discusses the development of an intelligent employer matching system based on multifactor analysis. The system uses a career test that evaluates 40 factors, divided into four categories: career development, work environment, social and corporate benefits, and personal values and lifestyle. Machine learning algorithms account for the interconnections between attributes and provide personalized recommendations for students and young professionals. The test results are compared with employer profiles, created based on feedback from company employees. The system is planned to integrate with platforms that scrape job postings from popular websites like dou.ua, which will increase its relevance. Implementing this system will help optimize the employment process and facilitate more accurate matching of specialists to the labor market's needs.