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GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints

Summary: GooseDB combines DuckDB with an MILP solver to synthesize minimally modified SQL queries that enforce representation (group-count) constraints on top-k outputs given constraints and user modification preferences. Novelty: supports broad edits to selection predicates and scoring functions and is the first system to jointly optimize both (and across multiple k) for minimal-change refinements, substantially generalizing prior work. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h87a657befe12fe24
Venue
VLDB
Year
2025
Pagerank
4.9793485e-05
Overall Rank
11,405 | 23.32%
DOI
10.14778/3750601.3750669

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Authors

BibTeX Citation

@article{chen_vldb25,
        title = {{GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints}},
        author = {Chen, Zixuan and Li, Jinyang and Jagadish, H. V. and Riedewald, Mirek},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {12},
        pages = {5351--5354},
        doi = {10.14778/3750601.3750669},
        url = {https://doi.org/10.14778/3750601.3750669},
        year = {2025}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
71 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00037720227
1,379 Designing Fair Ranking Schemes 2019 SIGMOD 0.0001086418
4,327 Query Refinement for Diversity Constraint Satisfaction 2024 VLDB 6.6632438e-05
5,353 Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals 2023 VLDB 6.1637765e-05
6,520 Query Refinement for Diverse Top-k Selection 2024 SIGMOD 5.7573717e-05
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