Querying Incomplete Numerical Data: Between Certain and Possible Answers
Summary: Model numerical nulls as marked nulls with probability distributions, yielding probabilistic bag DBs with repeated-null correlations and compositional semantics for arithmetic and aggregate queries. Show queries are measurable with finite outputs, and provide efficient approximations for output-interval probabilities (exact computation intractable). (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Marco Console
- 2. Leonid Libkin
- 3. Liat Peterfreund
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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 |
|---|---|---|---|---|
| 321 | MCDB: A Monte Carlo Approach to Managing Uncertain Data | 2008 | SIGMOD | 0.00027527389 |
| 2,331 | Orion 2.0: Native Support for Uncertain Data | 2008 | SIGMOD | 9.018559e-05 |
| 2,875 | MayBMS: A Probabilistic Database Management System | 2009 | SIGMOD | 7.9742313e-05 |
| 4,148 | A Formal Semantics of SQL Queries, Its Validation, and Applications | 2018 | VLDB | 6.4079361e-05 |
| 7,939 | Tuple-Independent Representations of Infinite Probabilistic Databases | 2021 | PODS | 4.613363e-05 |
| 7,941 | Efficient Uncertainty Tracking for Complex Queries with Attribute-level Bounds | 2021 | SIGMOD | 4.613363e-05 |
| 8,803 | Coping with Incomplete Data: Recent Advances | 2020 | PODS | 4.4470842e-05 |
| 8,947 | Queries with Arithmetic on Incomplete Databases | 2020 | PODS | 4.4248197e-05 |
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