Recommendation System for Enhanced Customer Experience: A Novel Image-to-Text Method
Keywords: Fashion recommendation, Recommendation systems, Visual search, Multimodal AI
Abstract: Existing fashion recommendation systems encounter difficulties in using visual
data for accurate and personalized recommendations. This research describes an in-
novative 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 de-
scriptions emphasizing stylistic elements. These captions guide retrieval from a
global fashion product catalog to offer similar alternatives that fit the visual charac-
teristics 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.
Submission Category: Machine learning algorithms
Submission Number: 63
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