Collaborative filtering approach in recommender systems: Study and Analysis

Kawtar Najmani; Nawal Sael; Ahmed Zellou; Academic Editor: Youssef EL FOUTAYENI

Research Communication | Open Access
Volume 2019 | Communication ID 132

Collaborative filtering approach in recommender systems: Study and Analysis

Kawtar Najmani, Nawal Sael, Ahmed Zellou, El Habib Benlahmar

Academic Editor: Youssef EL FOUTAYENI

Received	Accepted	Published
Jan 29, 2019	Feb 26, 2019	Mar 01, 2019

Abstract: Recommender systems aim to present to a user the items which may interest him. Their main aim is to utilize the various sources of data to infer customer interests [1]. Currently, they are proposed in several domains, namely: e-commerce, e-learning, research, music, social networks, etc. There are mainly three approaches that are used in the recommender systems: the content based filtering, the collaborative filtering, which is one of the most widely used and successful approach in the recommendation field by far [2], and the hybrid filtering. In this work, we present a detailed analytical ...