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Understanding Cardinality Estimation using Entropy Maximization

Summary: Principled MaxEnt framework for cardinality estimation: treat given query statistics as constraints on a distribution over possible worlds and pick the maximum-entropy model. Develops the mathematical tools to apply MaxEnt to predict conjunctive-query cardinalities, enabling systematic inference from arbitrary statistical assertions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1507
Venue
PODS
Year
2010
Pagerank
5.240797e-05
Overall Rank
5,983 | 58.42%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
1,727 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00010731889
2,295 Data Generation using Declarative Constraints 2011 SIGMOD 9.0842571e-05
7,875 Probabilistic Database Summarization for Interactive Data Exploration 2017 VLDB 4.6262777e-05
11,993 Online Ordering of Overlapping Data Sources 2014 VLDB 4.1905499e-05
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Showing 11 of 11 cited papers.

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

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