Aggregates in Possibilistic Databases
Summary: Proposes a possibilistic/fuzzy framework for aggregates over imprecise data, filling a gap in uncertainty-aware query processing. Defines scalar aggregates and aggregate functions; supports three regimes—approximate on precise data, precise on possibilistic data, and vague on imprecise data—via the extension principle and possibilistic expected value. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,771 | Offering a Precision-Performance Tradeoff for Aggregation Queries over Replicated Data | 2000 | VLDB | 0.00010606967 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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