HKUDS/XRec
[EMNLP'2024] "XRec: Large Language Models for Explainable Recommendation"
This project helps e-commerce managers and content curators improve their recommendation systems by providing clear, human-readable explanations for why certain items are recommended to a user. It takes existing user and item profiles, along with past interactions, and generates a tailored explanation for each recommendation. This is ideal for anyone managing online product catalogs or content platforms who wants to increase user trust and engagement.
170 stars. No commits in the last 6 months.
Use this if you manage a recommendation system and need to automatically generate clear, personalized explanations for why a user is seeing a particular recommendation.
Not ideal if you are looking for a recommendation engine to generate the recommendations themselves, rather than explanations for existing ones.
Stars
170
Forks
29
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 24, 2024
Commits (30d)
0
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