A Novel Recommender System based on Two-level Friendship Ties within Social Learning

Sonia Souabi, Asmaâ Retbi, Mohammed Idrissi, Samir Bennani

2021

Abstract

Nowadays, social networks are starting to emerge as a huge part of e-learning. Indeed, learners are more attracted to social learning environments that foster collaboration and interaction among learners. To enable learners to handle their time and energy more effectively, recommendation systems tend to address these issues and provide learners with a set of recommendations appropriate to their needs and requirements. To this end, we propose a recommendation system based on the correlation and co-occurrence between the activities performed by the learners on one hand, and on the other hand, based on the community detection based on two-level friendship ties. The idea is to detect communities based on friends and friends of friends, and then generate recommendations for each community detected. We test our approach on a database of 3000 interactions and it turns out that the two-level recommendation system based on friendships reaches a high accuracy and performs better results than the recommendation system based one level friendship ties in terms of precision as well as accuracy. It turns out that expanding the detected communities to generate new communities leads to more relevant and reliable results.

Paper Citation

in Harvard Style

Souabi S., Retbi A., Idrissi M. and Bennani S. (2021). A Novel Recommender System based on Two-level Friendship Ties within Social Learning. In Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-523-4, pages 566-573. DOI: 10.5220/0010599605660573

in Bibtex Style

@conference{icsoft21,
author={Sonia Souabi and Asmaâ Retbi and Mohammed Idrissi and Samir Bennani},
title={A Novel Recommender System based on Two-level Friendship Ties within Social Learning},
booktitle={Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2021},
pages={566-573},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010599605660573},
isbn={978-989-758-523-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - A Novel Recommender System based on Two-level Friendship Ties within Social Learning
SN - 978-989-758-523-4
AU - Souabi S.
AU - Retbi A.
AU - Idrissi M.
AU - Bennani S.
PY - 2021
SP - 566
EP - 573
DO - 10.5220/0010599605660573