Rodeo: Making Refinements for Diverse Top-k Queries

Felix S. Campbell, Julia Stoyanovich, Yuval Moskovitch

Research output: Contribution to journalConference articlepeer-review

Abstract

Database queries are commonly used to select and rank items. With the increasing awareness of diversity, ensuring a diverse output (i.e., the representation of different groups in the top-k positions) becomes essential. To address this challenge, we present Rodeo, a system that generates minimal modifications to queries to enhance the diversity of the ranking they produce based on constraints over groups’ representation in the top-k for various k values.

Original languageEnglish
Pages (from-to)4341-4344
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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