Recommendation System for E-Learning and E-Commerce Using Machine Learning

Shabana, Sreyalakshmi P., Tharun B., Vyshnavi M., Sameer

2025

Abstract

Recommender systems have become an essential component of modern e-learning and e-retail platforms, providing personalized content recommendations to enhance user engagement and satisfaction. Traditional recommendation techniques, for example, methods like content-based filtering and collaborative filtering, suffer from drawbacks like the new user problem, limited data density, and overspecialization. To address these obstacles, this study proposes a combined recommender structure that integrates multiple techniques, including content-based and collaborative filtering, along with advanced machine learning algorithms. The proposed system leverages matrix factorization, TF-IDF vectorization, and deep learning models to refine recommendations and adapt to dynamic user preferences. Experimental evaluation using key performance indicators like exactness, retrieval rate, F1-measure, and average prediction error (APE) demonstrates that the hybrid approach significantly improves recommendation accuracy compared to standalone methods. The findings highlight the potential of hybrid recommender systems in enhancing personalized learning experiences, optimizing product recommendations, and improving overall platform efficiency. Future research directions include exploring real-time adaptability, reinforcement learning, and contextual awareness to further refine recommendation accuracy and user engagement.

Paper Citation

in Harvard Style

Shabana., P. S., B. T., M. V. and Sameer. (2025). Recommendation System for E-Learning and E-Commerce Using Machine Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 100-105. DOI: 10.5220/0013923400004919

in Bibtex Style

@conference{icrdicct`2525,
author={Shabana and Sreyalakshmi P. and Tharun B. and Vyshnavi M. and Sameer},
title={Recommendation System for E-Learning and E-Commerce Using Machine Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={100-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013923400004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Recommendation System for E-Learning and E-Commerce Using Machine Learning
SN - 978-989-758-777-1
AU - Shabana.
AU - P. S.
AU - B. T.
AU - M. V.
AU - Sameer.
PY - 2025
SP - 100
EP - 105
DO - 10.5220/0013923400004919
PB - SciTePress