Special Issue on Algorithmic Bias and Fairness in Search and Recommendation

Special Issue on Algorithmic Bias and Fairness in Search and Recommendation

May 18, 2020

Given the increasing adoption of systems empowered with search and recommendation capabilities, it is crucial to ensure that their decisions do not lead to biased or even discriminatory outcomes. Controlling the effects generated by popularity bias to improve the user’s perceived quality of the results, supporting consumers and providers with fair rankings and recommendations, and providing transparent results are examples of challenges that require attention. This special issue intends to bring together original research methods and applications that put people first, inspect social and ethical impacts, and uplift the public’s trust on search and recommendation technologies. The goal is to favor a community-wide dialogue on new research perspectives in this field. Guest editorial of the IPM special issue

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