Search Results for author: Dina Zilbershtein

Found 1 papers, 0 papers with code

VideolandGPT: A User Study on a Conversational Recommender System

no code implementations7 Sep 2023 Mateo Gutierrez Granada, Dina Zilbershtein, Daan Odijk, Francesco Barile

This paper investigates how large language models (LLMs) can enhance recommender systems, with a specific focus on Conversational Recommender Systems that leverage user preferences and personalised candidate selections from existing ranking models.

Fairness Recommendation Systems

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