LehengTHU/AlphaRec
[ICLR 2025 Oral 🏆] The implementation of paper "Language Representations Can be What Recommenders Need: Findings and Potentials"
This project helps e-commerce and content platform managers build highly effective recommendation systems quickly. By leveraging advanced language models, it takes item descriptions and user interaction data to generate product recommendations that are more relevant and responsive to changing user interests. Online retailers and media streaming services can use this to improve customer satisfaction and sales.
No commits in the last 6 months.
Use this if you need to build or enhance a recommendation system that quickly adapts to user intentions and performs well even with new items or in new product categories.
Not ideal if you don't have detailed textual descriptions for your items or if your primary goal is not improving recommendation accuracy and speed.
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Language
Python
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Last pushed
May 16, 2025
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