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NetCube: A Scalable Tool for Fast Data Mining and Compression

Summary: NetCube uses Bayesian networks to model the joint distribution and yield approximate counts for don't-care queries, leveraging correlations. Linear preprocessing; constant-time estimates; high compression (1800:1) with low reconstruction error, enabling fast mining. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8756
Venue
VLDB
Year
2001
Pagerank
4.5808537e-05
Overall Rank
8,108 | 43.65%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,372 Sample Debiasing in the Themis Open World Database System 2020 SIGMOD 6.2367043e-05
6,329 Efficient Construction of Approximate Ad-Hoc ML models Through Materialization and Reuse 2018 VLDB 5.1030159e-05
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Showing 9 of 9 cited papers.

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

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