Recommender systems are a subclass of information filtering systems, used to predict how users would rate or score particular objects (movies, music, merchandise, etc.). Recommender systems filter large volumes of information based on the data provided by a user and other factors, and they take care of the user’s preference and interest.
Recommender systems utilize algorithms that optimize the analysis of the data to build the recommendations. They ensure a high level of efficiency as they can associate elements of our consumption profiles such as purchase history, content selection, and even our hours of activity, to make accurate recommendations.