Discovering Denial Constraints
Summary: Proposes Denial Constraints (DCs) as a more expressive integrity-constraint language than FDs/CFDs, with sound inference rules and a linear-time implication test. Devotes an instance-driven DC discovery algorithm and a novel scoring function to rank candidates for user validation; empirical evaluation on real and synthetic data demonstrates scalable, effective constraint discovery. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xu Chu
- 2. Ihab F. Ilyas
- 3. Paolo Papotti
Incoming Citations (Sorted by Pagerank)
Showing 21 of 71 citing papers.
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 |
|---|---|---|---|---|
| 13 | Mining Association Rules between Sets of Items in Large Databases | 1993 | SIGMOD | 0.0010864752 |
| 224 | CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies | 2004 | SIGMOD | 0.00032746205 |
| 475 | Mining Database Structure; Or, How to Build a Data Quality Browser | 2002 | SIGMOD | 0.00022303253 |
| 732 | Discovering Data Quality Rules | 2008 | VLDB | 0.00017465093 |
| 1,188 | On Generating Near-Optimal Tableaux for Conditional Functional Dependencies | 2008 | VLDB | 0.00013441729 |
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