AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method
Abstract
Existing fashion recommendation systems encounter difficulties in using visual data for accurate and personalized recommendations. This research describes an innovative end-to-end pipeline that uses artificial intelligence to provide fine-grained visual interpretation for fashion recommendations. When customers upload images of desired products or outfits, the system automatically generates meaningful descriptions emphasizing stylistic elements. These captions guide retrieval from a global fashion product catalogue to offer similar alternatives that fit the visual characteristics of the original image. On a dataset of over 100,000 categorized fashion photos, the pipeline was trained and evaluated. The F1-score for the object detection model was 0.97, exhibiting exact fashion object recognition capabilities optimized for recommendation. This visually aware system represents a key advancement in customer engagement through personalized fashion recommendations
Cite
@article{arxiv.2311.09624,
title = {AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method},
author = {Mohamaed Foued Ayedi and Hiba Ben Salem and Soulaimen Hammami and Ahmed Ben Said and Rateb Jabbar and Achraf CHabbouh},
journal= {arXiv preprint arXiv:2311.09624},
year = {2023}
}
Comments
6 pages, 5 figures