Modeling an e-Commerce Hybrid Recommender System Based on Machine Learning Algorithms

Antonio Panarese, Giuseppina Settanni, Angelo Galiano

2023

Abstract

The spread of the Web and the digitalization of human society has led to the emergence of e-commerce sites. The remarkable increase in the amount of data produced by digital and automated devices forces the use of intelligent algorithms capable of processing the collected data in order to extract information. In particular, machine learning algorithms give the possibility to implement automatic models to process data and provide personalized suggestions. The advanced recommender systems are based on these models that make companies, which use the e-commerce channel, able to provide the users with suggestions on products they may be interested in. This paper proposes a model of hybrid recommender system based on the use of clustering algorithms and XGBoost, respectively, to perform a preliminary segmentation of item-customer data and predict user preference. The implemented model is discussed and preliminarily validated through a test performed using the data of a statistical sample made up of regular users of an e-commerce site.

Paper Citation

in Harvard Style

Panarese A., Settanni G. and Galiano A. (2023). Modeling an e-Commerce Hybrid Recommender System Based on Machine Learning Algorithms. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 706-712. DOI: 10.5220/0011745700003393

in Bibtex Style

@conference{icaart23,
author={Antonio Panarese and Giuseppina Settanni and Angelo Galiano},
title={Modeling an e-Commerce Hybrid Recommender System Based on Machine Learning Algorithms},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={706-712},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011745700003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Modeling an e-Commerce Hybrid Recommender System Based on Machine Learning Algorithms
SN - 978-989-758-623-1
AU - Panarese A.
AU - Settanni G.
AU - Galiano A.
PY - 2023
SP - 706
EP - 712
DO - 10.5220/0011745700003393