AI Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method

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. Wh...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2023-11
Main Authors: Ayedi, Mohamaed Foued, Hiba Ben Salem, Hammami, Soulaimen, Ahmed Ben Said, Jabbar, Rateb, CHabbouh, Achraf
Format: Article
Language:English
Subjects:
Artificial intelligence
Customer satisfaction
Customization
Image enhancement
Object recognition
Recommender systems
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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
ISSN:2331-8422