liuqidong07/LLM-ESR
[NeurIPS'24 Spotlight] The official implementation code of LLM-ESR.
This project helps e-commerce managers and product strategists improve their recommendation systems, especially for niche products or new users. It takes raw user interaction data (like purchases or reviews) and product/user descriptions, then outputs enhanced recommendation models. The primary users are data scientists or machine learning engineers working on personalized recommendations.
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Use this if you need to build more accurate sequential recommendation systems that perform well even for less popular items or users with limited interaction history.
Not ideal if you are looking for a plug-and-play recommendation engine without deep technical involvement in model training and data preprocessing.
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Language
Python
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MIT
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Last pushed
Jun 27, 2024
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