A Review on Job Recommendation System

Abstract

With the rapid growth of artificial intelligence and machine learning technologies, the recommendation system aims to help users find items that match their preferences. In order to improve performance, many recommendation system techniques have been proposed. This paper presents a survey of some common recommendation techniques and related issues with advantages and disadvantages. At the same time, the different types of job recommendation systems are described in detail and compared with each other. The goal is to provide a comprehensive overview of the current state of job recommendation systems and to analyze the characteristics of each system. The results of the case studies can contribute to a better understanding of the strengths and weaknesses, as well as techniques used in different job recommendation systems. Through this review, insights are provided to guide the development of more effective recommendation systems. For future research, a system is proposed to generate career move recommendations with upskilling and reskilling suggestions.