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Efficient k-Regret Query Algorithm with Restriction-free Bound for any Dimensionality

Summary: Lower bound on the maximum regret ratio for k-regret queries; Sphere, a restriction-free algorithm that works in arbitrary dimensionality. Asymptotically optimal upper bound on regret, outperforming state-of-the-art methods in extensive experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5549
Venue
SIGMOD
Year
2018
Pagerank
5.6013035e-05
Overall Rank
5,255 | 63.45%
DOI
10.1145/3183713.3196903

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Showing 10 of 10 cited papers.

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

Rank Cited Paper Year Venue Pagerank
430 The Onion Technique: Indexing for Linear Optimization Queries 2000 SIGMOD 0.00023463938
914 Finding k-Dominant Skylines in High Dimensional Space 2006 SIGMOD 0.00015387584
1,072 Regret-Minimizing Representative Databases 2010 VLDB 0.00014270817
1,445 Diversifying Top-K Results 2012 VLDB 0.00011945231
1,998 Discovering Relative Importance of Skyline Attributes 2009 VLDB 9.824482e-05
2,478 Computing k-Regret Minimizing Sets 2014 VLDB 8.6927744e-05
2,480 Top-k Bounded Diversification 2012 SIGMOD 8.6899714e-05
2,615 Interactive Regret Minimization 2012 SIGMOD 8.4473503e-05
5,116 Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative 2017 SIGMOD 5.6830089e-05
5,904 k-Regret Queries with Nonlinear Utilities 2015 VLDB 5.2790141e-05
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