Recommendation System and Its Techniques in Machine Learning: A Survey

Abstract

Machine learning-based recommendation systems are formidable tools that target specific customers with tailored product and content recommendations based on their user data and behavioural patterns. Due to the abundance of information available today, it is now challenging to separate out and provide the user with the most pertinent information. Therefore, using recommendation systems to reduce time and costs for both the business and the user is now necessary to address the issue of information overload. Based on a user’s interest and past preferences, these systems might suggest suitable products to them, thus increasing revenue. This paper seeks to clarify the idea of the recommendation systems built upon, the many methods used to create these systems and the necessity of using these systems in the current and future environments.