Bellwether Analysis: Predicting Global Aggregates from Local Regions

Summary: Bellwether analysis for predicting global aggregates from local regions by learning from query-defined labels on partially labeled data. It uses small, cost-efficient bellwether subsets to project those labels onto future data without re-labelling the entire corpus. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9479
Venue: VLDB
Year: 2006
Pagerank: 4.5669241e-05
Overall Rank: 8,179 | 43.11%
DOI: -

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,794	Towards Keyword-Driven Analytical Processing	2007	SIGMOD	8.1140341e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
11	Implementing Data Cubes Efficiently	1996	SIGMOD	0.0011708144
472	Bottom-Up Computation of Sparse and Iceberg CUBEs	1999	SIGMOD	0.00022346384
1,455	RainForest - A Framework for Fast Decision Tree Construction of Large Datasets	1998	VLDB	0.00011899821
1,955	Efficient Computation of Iceberg Cubes with Complex Measures	2001	SIGMOD	9.9629452e-05
2,448	Multi-Dimensional Regression Analysis of Time-Series Data Streams	2002	VLDB	8.8032353e-05
6,641	Prediction Cubes	2005	VLDB	4.97969e-05
12,520	Composite Subset Measures	2006	VLDB	4.1945683e-05

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