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Bradley-Terry Rankings for Recommender Systems Across Dataset Taxonomies

paperactivebradley-terry-rankings-for-recommender-systems-across-dataset-taxonomies-ba4cd94d·1 events·first seen Jun 8, 2026

Aliases: Bradley-Terry Rankings for Recommender Systems Across Dataset Taxonomies

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NDCG

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Recent events (1)

3arXiv · cs.LG·Jun 8, 2026·source ↗

Bradley-Terry model proposed for fairer ranking of recommendation algorithms across dataset types

A new arXiv preprint introduces a Bradley-Terry (BT) model-based methodology for ranking recommendation algorithms in a way that accounts for dataset characteristics such as sparsity, sequential structure, and scale. The authors argue that naive metric aggregation (e.g., averaging NDCG) produces misleading rankings and propose BT trees and covariate-extended BT models as alternatives. The framework also enables ranking predictions on unseen datasets without running the models, and includes a new metric for ranking consistency.

Evaluation and Benchmarking Bradley-Terry Rankings for Recommender Systems Across Dataset Taxonomies NDCG