Empowering Few-Shot Recommender Systems With Large Language Models-Enhanced Representations

Empowering Few-Shot Recommender Systems With Large Language Models-Enhanced Representations

Recommender systems utilizing explicit feedback have witnessed significant advancements and widespread applications over the past years. However, generating recommendations in few-shot scenarios remains a persistent challenge. Recently, large language models (LLMs) have emerged as a promising soluti...

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Bibliographic Details
Main Author: Zhoumeng Wang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Large language models
recommender systems
ChatGPT
representations
Online Access:https://ieeexplore.ieee.org/document/10440582/

Internet

https://ieeexplore.ieee.org/document/10440582/

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