loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Mohammed Tadlaoui 1 ; Karim Sehaba 2 and Sébastien George 3

Affiliations: 1 Université de Tlemcen and INSA de Lyon, Algeria ; 2 Université de Lyon, France ; 3 LUNAM Université and Université du Maine, France

Keyword(s): Recommender Systems, Educational Resources, Social Networks, Social Influence.

Related Ontology Subjects/Areas/Topics: Collaborative Learning ; Computer-Supported Education ; e-Learning ; e-Learning Platforms ; Simulation and Modeling ; Simulation Tools and Platforms ; Social Context and Learning Environments ; Theoretical Bases of e-Learning Environments

Abstract: Recommender systems are able to estimate the interest for a user of a given resource from some information about similar users and resources properties. In our work, we focus on the recommendations of educational resources in the field of Technology Enhanced Learning (TEL) and more specifically the recommendations which are based on social information. Based on the results of research in recommender systems and TEL, we define an approach to recommend learning resources using social information present in social networks. We have developed a formal model for the calculation of similarity between users and the generation of three types of recommendation. We also developed a platform that implements our approach.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.145.105.149

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tadlaoui, M.; Sehaba, K. and George, S. (2015). Recommendation of Learning Resources based on Social Relations. In Proceedings of the 7th International Conference on Computer Supported Education - CSEDU; ISBN 978-989-758-108-3; ISSN 2184-5026, SciTePress, pages 425-432. DOI: 10.5220/0005452304250432

@conference{csedu15,
author={Mohammed Tadlaoui. and Karim Sehaba. and Sébastien George.},
title={Recommendation of Learning Resources based on Social Relations},
booktitle={Proceedings of the 7th International Conference on Computer Supported Education - CSEDU},
year={2015},
pages={425-432},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005452304250432},
isbn={978-989-758-108-3},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Computer Supported Education - CSEDU
TI - Recommendation of Learning Resources based on Social Relations
SN - 978-989-758-108-3
IS - 2184-5026
AU - Tadlaoui, M.
AU - Sehaba, K.
AU - George, S.
PY - 2015
SP - 425
EP - 432
DO - 10.5220/0005452304250432
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic