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 |
|---|---|---|---|---|
| 1,597 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00011209846 |
| 5,024 | Towards Distribution-aware Query Answering in Data Markets | 2022 | VLDB | 5.7535043e-05 |
| 5,555 | On Obtaining Stable Rankings | 2019 | VLDB | 5.4386174e-05 |
| 7,002 | Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable Size | 2021 | SIGMOD | 4.8670742e-05 |
| 9,246 | Happiness Maximizing Sets under Group Fairness Constraints | 2023 | VLDB | 4.3690661e-05 |
| 9,775 | Interactive Search for One of the Top-k | 2021 | SIGMOD | 4.2856106e-05 |
| 10,223 | On Fair Epsilon Net and Geometric Hitting Set | 2026 | VLDB | 4.1945683e-05 |
| 10,555 | Mining the Minoria: Unknown, Under-represented, and Under-performing Minority Groups | 2025 | VLDB | 4.1945683e-05 |
| 11,195 | rkHit: Representative Query with Uncertain Preference | 2023 | SIGMOD | 4.1945683e-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 |
|---|---|---|---|---|
| 2,615 | Interactive Regret Minimization | 2012 | SIGMOD | 8.4473503e-05 |
| 11,195 | rkHit: Representative Query with Uncertain Preference | 2023 | SIGMOD | 4.1945683e-05 |
| 7,632 | Rank Aggregation with Proportionate Fairness | 2022 | SIGMOD | 4.6915165e-05 |
| 5,255 | Efficient k-Regret Query Algorithm with Restriction-free Bound for any Dimensionality | 2018 | SIGMOD | 5.6013035e-05 |
| 5,904 | k-Regret Queries with Nonlinear Utilities | 2015 | VLDB | 5.2790141e-05 |
| 2,478 | Computing k-Regret Minimizing Sets | 2014 | VLDB | 8.6927744e-05 |
| 6,843 | Minimizing Average Regret Ratio in Database | 2016 | SIGMOD | 4.909799e-05 |
| 5,116 | Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative | 2017 | SIGMOD | 5.6830089e-05 |
| 1,072 | Regret-Minimizing Representative Databases | 2010 | VLDB | 0.00014270817 |
| 6,834 | A Unified Optimization Algorithm For Solving "Regret-Minimizing Representative" Problems | 2020 | VLDB | 4.9117328e-05 |