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)
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Authors
- 1. Zixuan Chen
- 2. Jinyang Li
- 3. H. V. Jagadish
- 4. Mirek Riedewald
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 185 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00036538405 |
| 1,597 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00011209846 |
| 5,649 | Query Refinement for Diverse Top-k Selection | 2024 | SIGMOD | 5.3911246e-05 |
| 5,826 | Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals | 2023 | VLDB | 5.3124507e-05 |
| 6,643 | Query Refinement for Diversity Constraint Satisfaction | 2024 | VLDB | 4.9786132e-05 |
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| 185 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00036538405 |
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