A Review of Techniques and Approaches Used in Recommendation System

Recommendation systems are automatic systems that allow, through machine learning algorithms, to offer users recommendations that align with their preferences and needs. It is a system capable of guiding users toward engaging interesting items within the existing content environment. It can also be considered as decreasing the time that the user takes to look for the most interesting products for him, so a recommendation system is focused on two main aspects. The first one is prediction: predicting the value of the ratings that a given customer has given to an item. The second is recommendation: a ranked list of items. Recommendation systems are often customized depending on the field of application, and will differ from one domain to another. This research has made a comparative study among various methods and techniques used for the recommendation system in order to finally propose a system adapted to our context, which is the recommendation system in e-learning.