Machine Learning Based Collaborative Filtering Using Jensen-Shannon Divergence for Context-Driven Recommendations

Jihene Latrech, Zahra Kodia, Nadia Ben Azzouna

2025

Abstract

This research presents a machine learning-based context-driven collaborative filtering approach with three steps: contextual clustering, weighted similarity assessment, and collaborative filtering. User data is clustered across 3 aspects, and similarity scores are calculated, dynamically weighted, and aggregated into a normalized User-User similarity matrix. Collaborative filtering is then applied to generate contextual recommendations. Experiments on the LDOS-CoMoDa dataset demonstrated good performance, with RMSE and MAE rates of 0.5774 and 0.3333 respectively, outperforming reference approaches.

Paper Citation

in Harvard Style

Latrech J., Kodia Z. and Ben Azzouna N. (2025). Machine Learning Based Collaborative Filtering Using Jensen-Shannon Divergence for Context-Driven Recommendations. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 419-426. DOI: 10.5220/0013146300003890

in Bibtex Style

@conference{icaart25,
author={Jihene Latrech and Zahra Kodia and Nadia Ben Azzouna},
title={Machine Learning Based Collaborative Filtering Using Jensen-Shannon Divergence for Context-Driven Recommendations},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={419-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013146300003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Machine Learning Based Collaborative Filtering Using Jensen-Shannon Divergence for Context-Driven Recommendations
SN - 978-989-758-737-5
AU - Latrech J.
AU - Kodia Z.
AU - Ben Azzouna N.
PY - 2025
SP - 419
EP - 426
DO - 10.5220/0013146300003890
PB - SciTePress