Real-Time, Scalable and Explainable Machine Learning for E-Commerce: Enhancing Product Recommendations and Customer Satisfaction with Ethical Intelligence

Bharath K., G. Chandramowleeswaran, Mohanraj P., L. Jothibasu, R. N. Bharani Versath, G. V. Rambabu

2025

Abstract

Recommendation systems and user satisfaction are of strategic importance for a business in the current scenario of e-commerce expansion and rapid changes in commercial environment. In this study, we introduce a real-time, scalable, and interpretable ML framework along with an e-commerce-ready application that personalizes product recommendation at a large scale. Our method differs from existing works, which are typically constrained to offline metrics, narrow datasets, cold-start settings, and shows strong performance under various domains, using multiple data sources such as multimodal data and multilingual contexts. With a focus on real-time inference, easy isntegration into business workflows, and using explainable AI methods to gain trust with and transparency for users. Secondly, the system is privacy-preserving (combining privacy with utility) and is guided by ethical considerations, as incorporates mechanisms to avoid exchanging content and bias avoiding approaches. Through thorough A/B testing and user satisfaction surveying, we show that the proposed model is capable to bring substantial improvements in customer engagement, conversion rates, and long-term retention.

Paper Citation

in Harvard Style

K. B., Chandramowleeswaran G., P. M., Jothibasu L., Versath R. and Rambabu G. (2025). Real-Time, Scalable and Explainable Machine Learning for E-Commerce: Enhancing Product Recommendations and Customer Satisfaction with Ethical Intelligence. 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 751-757. DOI: 10.5220/0013943200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Bharath K. and G. Chandramowleeswaran and Mohanraj P. and L. Jothibasu and R. Versath and G. Rambabu},
title={Real-Time, Scalable and Explainable Machine Learning for E-Commerce: Enhancing Product Recommendations and Customer Satisfaction with Ethical Intelligence},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={751-757},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013943200004919},
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 - Real-Time, Scalable and Explainable Machine Learning for E-Commerce: Enhancing Product Recommendations and Customer Satisfaction with Ethical Intelligence
SN - 978-989-758-777-1
AU - K. B.
AU - Chandramowleeswaran G.
AU - P. M.
AU - Jothibasu L.
AU - Versath R.
AU - Rambabu G.
PY - 2025
SP - 751
EP - 757
DO - 10.5220/0013943200004919
PB - SciTePress