Fairness in Preference Queries: Social Choice Theories Meet Data Management

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Abstract

Given a large number (notationally 𝑚) of users’ (members or voters) preferences as inputs over a large number of items or candidates (notationally 𝑛), preference queries leverage different preference aggregation methods to aggregate individual preferences in a systematic manner and come up with a single output (either a complete order or top-𝑘, ordered or unordered) that is most representative of the users’ preferences. The goal of this 1.5 hour lecture style tutorial is to adapt different preference aggregation methods from social choice theories, summarize how existing research has handled fairness over these methods, identify their limitations, and outline new research directions.