uoo723/PMGT
Implementation of "Pre-training Graph Transformer with Multimodal Side Information for Recommendation"
This project helps e-commerce businesses provide more accurate product recommendations to customers. It takes user interaction data (like past purchases or clicks), along with visual and textual information about products, and generates improved 'Top-N' product recommendations or predicts whether a customer will click on an item. The primary users are data scientists or machine learning engineers working on recommendation systems.
No commits in the last 6 months.
Use this if you are a data scientist looking to enhance your existing recommendation models by incorporating rich multimedia product information and graph-based pre-training.
Not ideal if you need an out-of-the-box recommendation system without any setup or if you don't have access to detailed multimodal (visual/textual) product data.
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Language
Python
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Last pushed
Mar 17, 2022
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