RRR: Rank-Regret Representative
Summary: Rank-Regret Representative (RRR): minimal subset ensuring at least one of the top-k items for every possible ranking function (rank-based regret). NP-hard; uses geometric bounds and combinatorial approximations to compute compact, scalable representatives, validated on real datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Abolfazl Asudeh
- 2. Azade Nazi
- 3. Nan Zhang
- 4. Gautam Das
- 5. H. V. Jagadish
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,577 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00011276814 |
| 5,022 | Towards Distribution-aware Query Answering in Data Markets | 2022 | VLDB | 5.7479778e-05 |
| 5,558 | On Obtaining Stable Rankings | 2019 | VLDB | 5.4375292e-05 |
| 6,988 | Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size | 2021 | SIGMOD | 4.8665394e-05 |
| 9,253 | Happiness Maximizing Sets under Group Fairness Constraints | 2023 | VLDB | 4.3648789e-05 |
| 9,755 | Interactive Search for One of the Top-k | 2021 | SIGMOD | 4.2856385e-05 |
| 10,223 | On Fair Epsilon Net and Geometric Hitting Set | 2026 | VLDB | 4.1905499e-05 |
| 10,564 | Mining the Minoria: Unknown, Under-represented, and Under-performing Minority Groups | 2025 | VLDB | 4.1905499e-05 |
| 11,197 | rkHit: Representative Query with Uncertain Preference | 2023 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,621 | Interactive Regret Minimization | 2012 | SIGMOD | 8.4408945e-05 |
| 11,197 | rkHit: Representative Query with Uncertain Preference | 2023 | SIGMOD | 4.1905499e-05 |
| 7,425 | Rank Aggregation with Proportionate Fairness | 2022 | SIGMOD | 4.7292787e-05 |
| 5,259 | Efficient k-Regret Query Algorithm with Restriction-free Bound for any Dimensionality | 2018 | SIGMOD | 5.5972902e-05 |
| 5,906 | k-Regret Queries with Nonlinear Utilities | 2015 | VLDB | 5.274596e-05 |
| 2,477 | Computing k-Regret Minimizing Sets | 2014 | VLDB | 8.6907684e-05 |
| 6,841 | Minimizing Average Regret Ratio in Database | 2016 | SIGMOD | 4.9057455e-05 |
| 5,113 | Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative | 2017 | SIGMOD | 5.6827696e-05 |
| 1,070 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014274615 |
| 6,816 | A Unified Optimization Algorithm For Solving "Regret-Minimizing Representative" Problems | 2020 | VLDB | 4.9115662e-05 |