The Use of Time Dimension in Recommender Systems for Learning

Eduardo José de Borba, Isabela Gasparini, Daniel Lichtnow

2017

Abstract

When the amount of learning objects is huge, especially in the e-learning context, users could suffer cognitive overload. That way, users cannot find useful items and might feel lost in the environment. Recommender systems are tools that suggest items to users that best match their interests and needs. However, traditional recommender systems are not enough for learning, because this domain needs more personalization for each user profile and context. For this purpose, this work investigates Time-Aware Recommender Systems (Context-aware Recommender Systems that uses time dimension) for learning. Based on a set of categories (defined in previous works) of how time is used in Recommender Systems regardless of their domain, scenarios were defined that help illustrate and explain how each category could be applied in learning domain. As a result, a Recommender System for learning is proposed. It combines Content-Based and Collaborative Filtering approaches in a Hybrid algorithm that considers time in Pre-Filtering and Post-Filtering phases.

Paper Citation

in Harvard Style

José de Borba E., Gasparini I. and Lichtnow D. (2017). The Use of Time Dimension in Recommender Systems for Learning . In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-248-6, pages 600-609. DOI: 10.5220/0006312606000609

in Bibtex Style

@conference{iceis17,
author={Eduardo José de Borba and Isabela Gasparini and Daniel Lichtnow},
title={The Use of Time Dimension in Recommender Systems for Learning},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2017},
pages={600-609},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006312606000609},
isbn={978-989-758-248-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - The Use of Time Dimension in Recommender Systems for Learning
SN - 978-989-758-248-6
AU - José de Borba E.
AU - Gasparini I.
AU - Lichtnow D.
PY - 2017
SP - 600
EP - 609
DO - 10.5220/0006312606000609