Projet de fin d'étude : Collaborative filtering approaches in recommender systems

Etudiant : EL YAGOUBY MOHAMED AMINE

Filière : LF Sciences Mathématiques et Informatique

Encadrant : Pr. NFAOUI EL HABIB

Annèe : 2022

Résumé : Recommender Systems have been around for the last few decades. It is a technology implemented in numerous commercial applications. Nowadays, consumers are presented with many choices. So, matching them with the most appropriate products is essential to improving their satisfaction and loyalty. The whole experience of the online shopping would be nowhere near what it is today without the contribution of recommender systems. This report represents the work we accomplished in our final study year project over a period of two months. We studied some of the different approaches that can be used in order to build a recommender system, including the one discovered in the 2006 Netflix competition. We also implemented these solutions in a web application that recommends numerous types of items. We called this application “SmartRecommender”.