Latent OLAP: Data Cubes over Latent Variables
Summary: Latent-variable cubes; aggregates over unobserved factors via Bayesian hierarchical models for OLAP. Defines the framework rigorously, addresses pitfalls of ignoring latent vars, and delivers efficient algorithms with experiments showing accuracy and speedups over baselines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Deepak Agarwal
- 2. Bee-Chung Chen
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 472 | Bottom-Up Computation of Sparse and Iceberg CUBEs | 1999 | SIGMOD | 0.00022346384 |
| 980 | BayesStore: Managing Large, Uncertain Data Repositories with Probabilistic Graphical Models | 2008 | VLDB | 0.00014879747 |
| 1,955 | Efficient Computation of Iceberg Cubes with Complex Measures | 2001 | SIGMOD | 9.9629452e-05 |
| 2,190 | Star-Cubing: Computing Iceberg Cubes by Top-Down and Bottom-Up Integration | 2003 | VLDB | 9.3317645e-05 |
| 2,268 | OLAP Over Uncertain and Imprecise Data | 2005 | VLDB | 9.1497575e-05 |
| 2,448 | Multi-Dimensional Regression Analysis of Time-Series Data Streams | 2002 | VLDB | 8.8032353e-05 |
| 3,549 | Optimizing MPF Queries: Decision Support and Probabilistic Inference | 2007 | SIGMOD | 6.9858057e-05 |
| 5,987 | Sampling Cube: A Framework for Statistical OLAP Over Sampling Data | 2008 | SIGMOD | 5.2432535e-05 |
| 6,641 | Prediction Cubes | 2005 | VLDB | 4.97969e-05 |
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