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Cleaning Uncertain Data with Quality Guarantees

Summary: Proposes PWS-quality, an ambiguity metric for probabilistic databases under possible-world semantics. Develops polynomial-time optimal cleaning to maximize PWS-quality by probing uncertain objects; efficient evaluation for independent and ranking queries, with practical heuristics. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9709
Venue
VLDB
Year
2008
Pagerank
5.4522327e-05
Overall Rank
5,537 | 61.49%
DOI
-

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