Papers with content-based filtering

1 papers
PepRec: Progressive Enhancement of Prompting for Recommendation (2024.emnlp-main)

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Challenge: Large language models (LLMs) have been gaining in-depth performance in natural language processing domains.
Approach: They propose a training-free prompting framework that captures knowledge from content-based filtering and collaborative filtering to boost recommendation performance with LLMs.
Outcome: The proposed framework outperforms traditional deep learning recommendation models and prompt-based recommendation systems on two real-world datasets.

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