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Revenue Maximization for Query Pricing

Summary: Revenue-maximization for query pricing under arbitrage-free constraints with single-minded buyers. Proposes new heuristics against known approximations; experiments show theory-tight bounds do not guarantee best practice, yielding fast, robust methods across distributions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12022
Venue
VLDB
Year
2020
Pagerank
6.2953388e-05
Overall Rank
4,279 | 70.24%
DOI
10.14778/3357377.3357378

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Showing 8 of 8 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,660 Data Markets in the Cloud: An Opportunity for the Database Community 2011 VLDB 0.00010979534
1,771 On Arbitrage-free Pricing for General Data Queries 2014 VLDB 0.00010617356
2,370 Query-Based Data Pricing 2012 PODS 8.9488834e-05
2,743 Toward Practical Query Pricing with QueryMarket 2013 SIGMOD 8.1897331e-05
2,820 Price-Optimal Querying with Data APIs 2016 VLDB 8.062913e-05
3,892 QIRANA: A Framework for Scalable Query Pricing 2017 SIGMOD 6.659352e-05
5,800 QueryMarket Demonstration: Pricing for Online Data Markets 2012 VLDB 5.3211601e-05
6,344 QIRANA Demonstration: Real Time Scalable Query Pricing 2017 VLDB 5.1023673e-05
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