Job Recommendation

Job recommendation systems aim to match job seekers with suitable opportunities, a task increasingly reliant on artificial intelligence. Current research focuses on improving recommendation accuracy and fairness by leveraging techniques like knowledge graphs, large language models (LLMs), and advanced machine learning algorithms such as reinforcement learning and optimal transport to address biases and personalize recommendations based on evolving user preferences and skills. These advancements hold significant potential to enhance efficiency in recruitment, reduce bias in hiring practices, and improve the job search experience for both employers and job seekers.