Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary)

Summary: Tutorial on learning and exploiting uncertain data at scale; probabilistic DBs, summaries, and decision-making under imprecision. Emphasizes DB constraints and optimization (convex, info-theory) under uncertainty, with scalable use-cases from sensors to cloud BI. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4191
Venue: SIGMOD
Year: 2009
Pagerank: 4.1945683e-05
Overall Rank: 12,311 | 14.36%
DOI: -

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
115	Eddies: Continuously Adaptive Query Processing	2000	SIGMOD	0.00046221215
477	Model-Driven Data Acquisition in Sensor Networks	2004	VLDB	0.00022221803
684	Towards a Robust Query Optimizer: A Principled and Practical Approach	2005	SIGMOD	0.00018179769
760	Creating Probabilistic Databases from Information Extraction Models	2006	VLDB	0.00017053935
1,043	Adaptive Ordering of Pipelined Stream Filters	2004	SIGMOD	0.00014476247
1,860	Approximation Algorithms for Clustering Uncertain Data	2008	PODS	0.0001028857
2,100	Query Optimization over Web Services	2006	VLDB	9.5443207e-05
3,445	Processing Forecasting Queries	2007	VLDB	7.08644e-05
4,192	Operator Placement for In-Network Stream Query Processing	2005	PODS	6.3727539e-05
5,850	Active and Accelerated Learning of Cost Models for Optimizing Scientific Applications	2006	VLDB	5.3009887e-05
12,299	Exceeding Expectations and Clustering Uncertain Data	2009	PODS	4.1945683e-05
12,480	Suppression and Failures in Sensor Networks: A Bayesian Approach	2007	VLDB	4.1945683e-05
12,488	Asking the Right Questions: Model-driven Optimization using Probes	2006	PODS	4.1945683e-05

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2,118	Using Probabilistic Models for Data Management in Acquisitional Environments	2005	CIDR	9.5100739e-05
8,087	Similarity Search and Mining in Uncertain Databases	2010	VLDB	4.5899317e-05
12,299	Exceeding Expectations and Clustering Uncertain Data	2009	PODS	4.1945683e-05
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