Fair Learning-to-Rank from Implicit Feedback

19 Nov 2019Himank YadavZhengxiao DuThorsten Joachims

Addressing unfairness in rankings has become an increasingly important problem due to the growing influence of rankings in critical decision making, yet existing learning-to-rank algorithms suffer from multiple drawbacks when learning fair ranking policies from implicit feedback. Some algorithms suffer from extrinsic reasons of unfairness due to inherent selection biases in implicit feedback leading to rich-get-richer dynamics... (read more)

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