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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)

Paper ID
h1675c07168f3941b
Venue
SIGMOD
Year
2019
Pagerank
5.6966108e-05
Overall Rank
6,721 | 54.83%
DOI
10.1145/3299869.3300080

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{asudeh_sigmod19,
        title = {{RRR: Rank-Regret Representative}},
        author = {Asudeh, Abolfazl and Nazi, Azade and Zhang, Nan and Das, Gautam and Jagadish, H. V.},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3300080},
        url = {https://dl.acm.org/doi/10.1145/3299869.3300080},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

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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.

Rank Cited Paper Year Venue Pagerank
5 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0010679903
342 The Onion Technique: Indexing for Linear Optimization Queries 2000 SIGMOD 0.00020520649
818 Finding k-Dominant Skylines in High Dimensional Space 2006 SIGMOD 0.00013666302
1,087 Regret-Minimizing Representative Databases 2010 VLDB 0.00012092041
1,379 Designing Fair Ranking Schemes 2019 SIGMOD 0.00010859038
2,106 Computing k-Regret Minimizing Sets 2014 VLDB 9.0287481e-05
2,545 Interactive Regret Minimization 2012 SIGMOD 8.3139128e-05
2,561 Answering Top-k Queries Using Views 2006 VLDB 8.2940439e-05
3,070 Towards Robust Indexing for Ranked Queries 2006 VLDB 7.6831067e-05
4,833 Efficient Computation of Regret-ratio Minimizing Set: A Compact Maxima Representative 2017 SIGMOD 6.3867086e-05
5,788 k-Regret Queries with Nonlinear Utilities 2015 VLDB 5.9926479e-05
7,034 Minimizing Average Regret Ratio in Database 2016 SIGMOD 5.614437e-05
8,554 Discovering the Skyline of Web Databases 2016 VLDB 5.3146691e-05
12,382 Query Reranking As A Service 2016 VLDB 4.9769913e-05
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