yuh-yang/MBHT-KDD22
[KDD'22] Multi-Behavior Hypergraph-Enhanced Transformer for Next-Item Recommendation
This helps e-commerce platforms and content providers recommend the next best item to a user by understanding their past interactions. It takes in a user's sequence of activities like clicks, adds-to-cart, or purchases, and outputs highly relevant next-item suggestions. This is for product managers, merchandisers, and data scientists building or improving recommendation systems.
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Use this if you need to generate highly accurate next-item recommendations based on diverse user behaviors beyond just purchases, considering the sequence and type of interactions.
Not ideal if your recommendation needs are simple, based on basic popularity or collaborative filtering, or if you don't have detailed multi-behavior user interaction data.
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70
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18
Language
Python
License
MIT
Category
Last pushed
May 09, 2023
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