Transforming E-Commerce: A Review of Machine Learning-Based Product Recommendation Systems

Abstract

Product suggestion systems have become more crucial in enhancing the shopping experience for customers and boosting revenues as e-commerce has grown quickly. By utilizing user data and behaviourto deliver tailored recommendations, machine learning-based systems have transformed the way products are recommended. We give a summary The most important idea is that the technology is state-of-the-art for machine learningbased product recommendation systems in this review paper. We go over various recommendation algorithm types, their advantages and disadvantages, and successful implementations. We also draw attention to the difficulties in putting these systems into practice and the moral issues raised by the exploitation of customer data. We conclude by sharing our perspectives on the evolution of product recommendation systems and their possible effects on e-commerce. The importance and promise of machine learning-based product recommendation systems in transforming e-commerce are fully understood in this review paper's overall framework