Achieving true fairness in recommender systems requires moving beyond broad demographic categories to address disparities at a fine-grained level, ensuring equitable representation for all subgroups. This goal can be made feasible through advanced re-ranking methodologies like CONFIGRE. Recommender systems are ubiquitous in today’s digital landscape, providing tailored suggestions to users in domains like e-commerce, entertainment, …
Day: January 28, 2025
User Perceptions of Diversity in Recommender Systems
Understanding user perceptions of diversity in recommender systems reveals a paradox: while users favor intuitive, metadata-driven metrics like genres, their ability to distinguish finer variations in diversity is limited, highlighting the need for user-aligned algorithms that balance diversity with relevance. In this study, in collaboration with Patrik Dokoupil and Ladislav Peska, and published in the …