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Optimizing Probabilistic Query Processing on Continuous Uncertain Data

Summary: Optimizes probabilistic threshold queries on continuous uncertain data with (i) new indexes to speed joins, (ii) dimensionality reduction and fast filters for selections, and (iii) a dynamic per-tuple query plan. Empirical results on real data and benchmarks show accuracy and substantial performance gains over state-of-the-art threshold optimizers. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10179
Venue
VLDB
Year
2011
Pagerank
4.6933659e-05
Overall Rank
7,623 | 46.97%
DOI
-

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