Quotient Cube: How to Summarize the Semantics of a Data Cube
Summary: Introduces the quotient cube: a lossless, lattice-preserving partition of cube cells into behaviorally equivalent regions, yielding concise semantic summaries. Provides scalable construction algorithms, optimal for monotone aggregates and locally optimal for non-monotone ones. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Laks V. S. Lakshmanan (University of British Columbia)
- 2. Jian Pei (Simon Fraser University)
- 3. Jiawei Han (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{lakshmanan_vldb02,
title = {{Quotient Cube: How to Summarize the Semantics of a Data Cube}},
author = {Lakshmanan, Laks V. S. and Pei, Jian and Han, Jiawei},
journal = {PVLDB},
series = {{VLDB} '02},
doi = {10.1016/B978-155860869-6/50074-3},
url = {https://doi.org/10.1016/B978-155860869-6/50074-3},
year = {2002}
}
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