Wang-Yu-Qing/EGES
DGL implementation of EGES
This project helps e-commerce platforms understand customer preferences and predict what items they might like. By taking information about products (SKUs), brands, shops, and categories, it generates 'embeddings' that represent each item. These embeddings can then be used to power recommendation systems, improving the shopping experience for customers.
No commits in the last 6 months.
Use this if you manage an e-commerce platform and want to generate better product recommendations for your users by leveraging rich item information.
Not ideal if your primary goal is not e-commerce recommendations or if you don't have detailed side information like brands, shops, and categories for your items.
Stars
31
Forks
8
Language
Python
License
—
Category
Last pushed
Mar 08, 2023
Commits (30d)
0
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