Exploring the Potential of Generative AI for Augmenting Choice-Based Preference Elicitation in Recommender Systems

Author:

Loepp Benedikt1ORCID,Ziegler Jürgen2ORCID

Affiliation:

1. Fraunhofer IMS, Germany

2. University of Duisburg-Essen, Germany

Publisher

ACM

Reference52 articles.

1. LLM Based Generation of Item-Description for Recommendation System

2. Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata

3. Oscar Luis Alvarado Rodriguez, Veronika Vanden Abeele, David Geerts, and Katrien Verbert. 2019. “I Really Don’t Know What ‘Thumbs Up’ Means”: Algorithmic Experience in Movie Recommender Algorithms. In Human-Computer Interaction — INTERACT 2019, David Lamas, Fernando Loizides, Lennart Nacke, Helen Petrie, Marco Winckler, and Panayiotis Zaphiris (Eds.). Lecture Notes in Computer Science, Vol. 11748. Springer, Berlin, Germany, 521–541.

4. Rate it again

5. Betul Ay and Galip Aydin. 2021. Visual Similarity-Based Fashion Recommendation System. In Generative Adversarial Networks for Image-to-Image Translation, Arun Solanki, Anand Nayyar, and Mohd Naved (Eds.). Academic Press, 185–203.

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