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Querying Uncertain Data with Aggregate Constraints

Summary: Uncertain data with aggregate constraints on record sets makes finding qualified possible worlds by per-tuple sampling inefficient. The paper proposes constraint-aware sampling and MCMC sampling to produce high-quality query results for uncertain data under aggregate constraints with reasonable cost. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4434
Venue
SIGMOD
Year
2011
Pagerank
5.2223439e-05
Overall Rank
6,079 | 57.72%
DOI
-

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