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MCDB: A Monte Carlo Approach to Managing Uncertain Data

Summary: MCDB: Monte Carlo framework for uncertain data. VG functions parameterized by SQL results store only parameters, not probabilities, and estimate distributions; supports joint distributions, queries, and functionals, via bundle-based processing. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4025
Venue
SIGMOD
Year
2008
Pagerank
0.00027527389
Overall Rank
321 | 97.77%
DOI
-

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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
14 Online Aggregation 1997 SIGMOD 0.0010801504
299 Trio: A System for Data, Uncertainty, and Lineage 2006 VLDB 0.00028525071
469 MauveDB: Supporting Model-based User Views in Database Systems 2006 SIGMOD 0.00022406923
760 Creating Probabilistic Databases from Information Extraction Models 2006 VLDB 0.00017053935
1,179 Probabilistic Skylines on Uncertain Data 2007 VLDB 0.00013457451
1,425 Scalable Approximate Query Processing With The DBO Engine 2007 SIGMOD 0.00012051353
1,705 U-DBMS: A Database System for Managing Constantly-Evolving Data 2005 VLDB 0.00010829958
2,978 Matching Twigs in Probabilistic XML 2007 VLDB 7.7845728e-05
3,372 OLAP over Imprecise Data with Domain Constraints 2007 VLDB 7.1683982e-05
3,929 Maximally Joining Probabilistic Data 2007 PODS 6.6248763e-05
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