Introduces the Mixture Linear Ordering Problem with mixed-integer programming formulations and a multi-start matheuristic to recover latent groups and their rankings from aggregate preference matrices.
Fair- ness in rankings and recommendations: an overview.VLDB Jour- nal, 31(3):431–458, 5 2022
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2roles
background 1polarities
background 1representative citing papers
The thesis identifies theoretical, empirical, and conceptual flaws in offline fairness measures for recommender systems and contributes new evaluation methods and practical guidelines.
citing papers explorer
-
Uncovering latent consensus in heterogeneous populations: The Mixture Linear Ordering Problem
Introduces the Mixture Linear Ordering Problem with mixed-integer programming formulations and a multi-start matheuristic to recover latent groups and their rankings from aggregate preference matrices.