Discovering Approximate Denial Constraints in Large Databases
Summary: LIMA discovers approximate denial constraints at scale using statistical inference over reduced samples and a restrictive validity criterion. It supports dynamic data, scales better in rows and attributes, and yields far fewer, substantially more precise constraints than prior methods. (summarized by gpt-5.6-luna on Aug 17 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Albert Martin (Universitat Politècnica de Catalunya)
- 2. Eduardo C. de Almeida (Federal University of Parana)
- 3. Oscar Romero (Universitat Politècnica de Catalunya)
- 4. Anna Queralt (Universitat Politècnica de Catalunya)
BibTeX Citation
@article{martin_vldb26,
title = {{Discovering Approximate Denial Constraints in Large Databases}},
author = {Martin, Albert and de Almeida, Eduardo C. and Romero, Oscar and Queralt, Anna},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {2086--2098},
doi = {10.14778/3819518.3819536},
url = {https://doi.org/10.14778/3819518.3819536},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,006 | LIMA: Denial Constraint Discovery in Large Dynamic Databases | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 33 | Consistent Query Answers in Inconsistent Databases | 1999 | PODS | 0.00049349003 |
| 350 | Discovering Denial Constraints | 2013 | VLDB | 0.00020253521 |
| 1,619 | Efficient Denial Constraint Discovery with Hydra | 2018 | VLDB | 0.00010055625 |
| 1,971 | Discovery of Approximate (and Exact) Denial Constraints | 2020 | VLDB | 9.2873596e-05 |
| 2,443 | Approximate Denial Constraints | 2020 | VLDB | 8.4586656e-05 |
| 4,067 | Fast Algorithms for Denial Constraint Discovery | 2023 | VLDB | 6.8216078e-05 |
| 5,280 | Fast Approximate Denial Constraint Discovery | 2023 | VLDB | 6.1992888e-05 |
| 11,319 | How and Why False Denial Constraints are Discovered | 2025 | VLDB | 4.9793485e-05 |
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|---|---|---|---|---|
| 1 | 10,058 | Discovering Approximate Inclusion Dependencies | 2025 | VLDB |
| 2 | 10,439 | Discovery of Denial Constraints with Hardware Acceleration | 2026 | SIGMOD |
| 3 | 11,319 | How and Why False Denial Constraints are Discovered | 2025 | VLDB |
| 4 | 350 | Discovering Denial Constraints | 2013 | VLDB |
| 5 | 5,280 | Fast Approximate Denial Constraint Discovery | 2023 | VLDB |
| 6 | 1,619 | Efficient Denial Constraint Discovery with Hydra | 2018 | VLDB |
| 7 | 2,443 | Approximate Denial Constraints | 2020 | VLDB |
| 8 | 4,067 | Fast Algorithms for Denial Constraint Discovery | 2023 | VLDB |
| 9 | 1,971 | Discovery of Approximate (and Exact) Denial Constraints | 2020 | VLDB |
| 10 | 11,006 | LIMA: Denial Constraint Discovery in Large Dynamic Databases | 2026 | VLDB |