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Bentrad, Sassi
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Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Enhancing recommendation diversity in e-commerce using siamese network and cluster-based technique Bahi, Abderaouf; Gasmi, Ibtissem; Bentrad, Sassi; Khantouchi, Ramzi
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8572

Abstract

This study investigates the difficulty of improving product recommendations in e-commerce systems by tackling the common problem of poor diversity in suggestions. We present a novel approach that uses a siamese network architecture and ResNet for feature extraction to recommend visually similar elements while incorporating diversity through a cluster-based mechanism. The Siamese network is used to compare product pairs, allowing it to recommend both comparable and dissimilar items from distinct clusters. The model was evaluated using a variety of evaluation metrics, resulting in an accuracy of 88.5%, a precision of 90.2%, a recall of 87.1%, and an F1 score of 88.6%. Our results demonstrate that our strategy maintains a high level of relevance in suggestions while efficiently incorporating variety, hence improving the overall user experience in e-commerce applications.
Co-Authors Bahi, Abderaouf Gasmi, Ibtissem Khantouchi, Ramzi