MOOCs Recommender System using Ontology and Memory-based Collaborative Filtering

Kahina Rabahallah, Latifa Mahdaoui, Faiçal Azouaou

2018

Abstract

With Massive Open Online Courses (MOOCs) proliferation, online learners are exposed to various challenges. Therefore, the lack of personalized recommendation of MOOCs can drive learners to choose irrelevant MOOCs and then lose their motivation and surrender the learning process. Recommender System (RS) plays an important role in assisting learners to find appropriate MOOCs to improve learners’ engagements and their satisfaction/completion rates. In this paper, we propose a MOOCs recommender system combining memory-based Collaborative Filtering (CF) techniques and ontology to recommend personalized MOOCs to online learners. In our recommendation approach, Ontology is used to provide a semantic description of learner and MOOC which will be incorporated into the recommendation process to improve the personalization of learner recommendations whereas CF computes predictions and generates recommendation. Furthermore, our hybrid approach can relieve the cold-start problem by making use of ontological knowledge before the initial data to work on are available in the recommender system.

Paper Citation

in Harvard Style

Rabahallah K., Mahdaoui L. and Azouaou F. (2018). MOOCs Recommender System using Ontology and Memory-based Collaborative Filtering.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-298-1, pages 635-641. DOI: 10.5220/0006786006350641

in Bibtex Style

@conference{iceis18,
author={Kahina Rabahallah and Latifa Mahdaoui and Faiçal Azouaou},
title={MOOCs Recommender System using Ontology and Memory-based Collaborative Filtering},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2018},
pages={635-641},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006786006350641},
isbn={978-989-758-298-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - MOOCs Recommender System using Ontology and Memory-based Collaborative Filtering
SN - 978-989-758-298-1
AU - Rabahallah K.
AU - Mahdaoui L.
AU - Azouaou F.
PY - 2018
SP - 635
EP - 641
DO - 10.5220/0006786006350641