Social Collaborative Filtering Approach for Recommending Courses in an E-learning Platform - Archive ouverte HAL Access content directly
Conference Papers Year : 2020

Social Collaborative Filtering Approach for Recommending Courses in an E-learning Platform

Abstract

In recent years, learning online using the e-learning platforms becomes indispensable in the teaching process. Companies and scientific researchers try to find new optimal methods and approaches that can improve education online. In this paper, we propose a new recommendation approach for recommending relevant courses to learners. Our method is based on social filtering and collaborative filtering for defining the best way in which the learner must learn, and recommend courses which better much the learner's profile and social content.
Fichier principal
Vignette du fichier
1-s2.0-S1877050919306337-main.pdf (378.54 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

hal-02468569 , version 1 (01-04-2020)

Licence

Attribution - NonCommercial - NoDerivatives - CC BY 4.0

Identifiers

Cite

Youness Madani, Mohammed Erritali, Jamaa Bengourram, Francoise Sailhan. Social Collaborative Filtering Approach for Recommending Courses in an E-learning Platform. International conference on Ambient Systems, Networks and Technologies (ANT), Apr 2019, leuven, Belgium. pp.1164-1169, ⟨10.1016/j.procs.2019.04.166⟩. ⟨hal-02468569⟩

Collections

CNAM CEDRIC-CNAM
66 View
224 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More