Fairness in Preference Queries: Social Choice Theories Meet Data Management

Senjuti Basu Roy, Baruch Schieber, Nimrod Talmon

Research output: Contribution to journalConference articlepeer-review

Abstract

Given a large number (notationallym) 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.

Original languageEnglish
Pages (from-to)4225-4228
Number of pages4
JournalProceedings of the VLDB Endowment
Volume17
Issue number12
DOIs
StatePublished - 1 Jan 2024
Event50th International Conference on Very Large Data Bases, VLDB 2024 - Guangzhou, China
Duration: 24 Aug 202429 Aug 2024

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Computer Science

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