Unbiased Offline Evaluation for Learning to Rank with Business Rules

no code implementations • 3 Nov 2023 • Matej Jakimov, Alexander Buchholz, Yannik Stein, Thorsten Joachims

For industrial learning-to-rank (LTR) systems, it is common that the output of a ranking model is modified, either as a results of post-processing logic that enforces business requirements, or as a result of unforeseen design flaws or bugs present in real-world production systems.

Learning-To-Rank Off-policy evaluation