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)
Incoming Non-self Citations Over Time
Authors
- 1. Min Xie
- 2. Raymond Chi-Wing Wong
- 3. Jian Li
- 4. Cheng Long
- 5. Ashwin Lall
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,816 | A Unified Optimization Algorithm For Solving "Regret-Minimizing Representative" Problems | 2020 | VLDB | 4.9115662e-05 |
| 6,988 | Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size | 2021 | SIGMOD | 4.8665394e-05 |
| 7,541 | Strongly Truthful Interactive Regret Minimization | 2019 | SIGMOD | 4.7104726e-05 |
| 8,812 | Creating Top Ranking Options in the Continuous Option and Preference Space | 2019 | VLDB | 4.4397776e-05 |
| 9,253 | Happiness Maximizing Sets under Group Fairness Constraints | 2023 | VLDB | 4.3648789e-05 |
| 9,753 | Minimum Coresets for Maxima Representation of Multidimensional Data | 2021 | PODS | 4.2856385e-05 |
| 9,754 | On m-Impact Regions and Standing Top-k Influence Problems | 2021 | SIGMOD | 4.2856385e-05 |
| 9,755 | Interactive Search for One of the Top-k | 2021 | SIGMOD | 4.2856385e-05 |
| 11,380 | Interactive Mining with Ordered and Unordered Attributes | 2022 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 428 | The Onion Technique: Indexing for Linear Optimization Queries | 2000 | SIGMOD | 0.0002349868 |
| 913 | Finding k-Dominant Skylines in High Dimensional Space | 2006 | SIGMOD | 0.00015372758 |
| 1,070 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014274615 |
| 1,435 | Diversifying Top-K Results | 2012 | VLDB | 0.00011981694 |
| 2,004 | Discovering Relative Importance of Skyline Attributes | 2009 | VLDB | 9.8183624e-05 |
| 2,474 | Top-k Bounded Diversification | 2012 | SIGMOD | 8.6956353e-05 |
| 2,477 | Computing k-Regret Minimizing Sets | 2014 | VLDB | 8.6907684e-05 |
| 2,621 | Interactive Regret Minimization | 2012 | SIGMOD | 8.4408945e-05 |
| 5,113 | Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative | 2017 | SIGMOD | 5.6827696e-05 |
| 5,906 | k-Regret Queries with Nonlinear Utilities | 2015 | VLDB | 5.274596e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,371 | Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data | 2007 | VLDB | 8.9443366e-05 |
| 7,541 | Strongly Truthful Interactive Regret Minimization | 2019 | SIGMOD | 4.7104726e-05 |
| 6,381 | k-Hit Query: Top-k Query with Probabilistic Utility Function | 2015 | SIGMOD | 5.0839387e-05 |
| 2,477 | Computing k-Regret Minimizing Sets | 2014 | VLDB | 8.6907684e-05 |
| 6,816 | A Unified Optimization Algorithm For Solving "Regret-Minimizing Representative" Problems | 2020 | VLDB | 4.9115662e-05 |
| 5,113 | Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative | 2017 | SIGMOD | 5.6827696e-05 |
| 2,621 | Interactive Regret Minimization | 2012 | SIGMOD | 8.4408945e-05 |
| 5,906 | k-Regret Queries with Nonlinear Utilities | 2015 | VLDB | 5.274596e-05 |
| 6,841 | Minimizing Average Regret Ratio in Database | 2016 | SIGMOD | 4.9057455e-05 |
| 1,070 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014274615 |