Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals

Summary: Defines 'why-not-yet' for top-k under linear scalarization: find weight vectors that would admit a target into top-k, casting it as satisfiability/optimization with potentially quantified, disjunctive, or negated constraints. Introduces a monotonic-core linear approximation and tunable algorithms to trade runtime for solution quality, demonstrating scalable empirical gains over the state of the art. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: hff9b6ebed91c5ae3
Venue: VLDB
Year: 2023
Pagerank: 6.140487e-05
Overall Rank: 5,374 | 63.98%
DOI: 10.14778/3598581.3598606
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Zixuan Chen (Northeastern University)
2. Panagiotis Manolios (Northeastern University)
3. Mirek Riedewald (Northeastern University)

BibTeX Citation

@article{chen_vldb23,
        title = {{Why Not Yet: Fixing a Top-k Ranking that Is Not Fair to Individuals}},
        author = {Chen, Zixuan and Manolios, Panagiotis and Riedewald, Mirek},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {9},
        pages = {2377--2390},
        doi = {10.14778/3598581.3598606},
        url = {https://doi.org/10.14778/3598581.3598606},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,534	Query Refinement for Diverse Top-k Selection	2024	SIGMOD	5.7356177e-05
9,520	Ranking Indicator Discovery from Very Large Knowledge Graphs	2025	VLDB	5.151324e-05
10,553	Local Stability of Rankings	2026	SIGMOD	4.9605343e-05
10,810	Database Views as Explanations for Relational Deep Learning	2026	VLDB	4.9605343e-05
11,464	GooseDB: A Database Engine that Optimally Refines Top-k Queries to Satisfy Representation Constraints	2025	VLDB	4.9605343e-05
11,662	Complex-Path: Effective and Efficient Node Ranking with Paths in Billion-Scale Heterogeneous Graphs	2024	VLDB	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
321	Making Database Systems Usable	2007	SIGMOD	0.00021093212
389	Why Not?	2009	SIGMOD	0.00019254758
419	PREFER: A System for the Efficient Execution of Multiparametric Ranked Queries	2001	SIGMOD	0.00018558415
581	The Complexity of Causality and Responsibility for Query Answers and non-Answers	2011	VLDB	0.00016042765
624	On the Provenance of Non-Answers to Queries over Extracted Data	2008	VLDB	0.00015438077
790	How to ConQueR Why-Not Questions	2010	SIGMOD	0.00013929166
1,055	Tiresias: The Database Oracle for How-To Queries	2012	SIGMOD	0.0001225364
1,385	Designing Fair Ranking Schemes	2019	SIGMOD	0.00010823535
2,079	Explaining Missing Answers to SPJUA Queries	2010	VLDB	9.0602682e-05
2,962	Reverse Data Management	2011	VLDB	7.7949147e-05
2,975	Answering Why-not Questions on Reverse Top-k Queries	2015	VLDB	7.7807277e-05
3,078	Towards Robust Indexing for Ranked Queries	2006	VLDB	7.6577871e-05
4,565	Identifying the Most Influential Data Objects with Reverse Top-k Queries	2010	VLDB	6.5178554e-05
4,577	HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach	2022	SIGMOD	6.5111757e-05
4,634	Branch-and-Bound Algorithm for Reverse Top-k Queries	2013	SIGMOD	6.476894e-05
4,638	QueryVis: Logic-based Diagrams help Users Understand Complicated SQL Queries Faster	2020	SIGMOD	6.4750914e-05
4,871	Explaining Wrong Queries Using Small Examples	2019	SIGMOD	6.3583165e-05
5,556	Putting Things into Context: Rich Explanations for Query Answers using Join Graphs	2021	SIGMOD	6.0705311e-05
5,624	On Obtaining Stable Rankings	2019	VLDB	6.0456849e-05
5,930	Reverse k-Ranks Query	2014	VLDB	5.9276255e-05
6,718	Toward Interpretable and Actionable Data Analysis with Explanations and Causality	2022	VLDB	5.6843134e-05
6,982	Scalable Package Queries in Relational Database Systems	2016	VLDB	5.6121014e-05
7,901	To Not Miss the Forest for the Trees - A Holistic Approach for Explaining Missing Answers over Nested Data	2021	SIGMOD	5.4136249e-05
9,090	Understanding Queries by Conditional Instances	2022	SIGMOD	5.2092307e-05
10,066	CaJaDE: Explaining Query Results by Augmenting Provenance with Context	2022	VLDB	5.074247e-05
10,067	Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb	2021	VLDB	5.074247e-05

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#	Overall Rank	Paper	Year	Venue
1	11,783	Equitable Top-k Results for Long Tail Data	2023	SIGMOD
2	7,348	Anytime Measures for Top-k Algorithms	2007	VLDB
3	3,116	Top-k Queries on Uncertain Data: On Score Distribution and Typical Answers	2009	SIGMOD
4	6,534	Query Refinement for Diverse Top-k Selection	2024	SIGMOD
5	9,431	Satisfying Complex Top-k Fairness Constraints by Preference Substitutions	2023	VLDB
6	6,191	Exact Processing of Uncertain Top-k Queries in Multi-criteria Settings	2018	VLDB
7	8,084	Evaluating Top-k Queries with Inconsistency Degrees	2020	VLDB
8	2,628	Ranking with Uncertain Scoring Functions: Semantics and Sensitivity Measures	2011	SIGMOD
9	1,385	Designing Fair Ranking Schemes	2019	SIGMOD
10	2,975	Answering Why-not Questions on Reverse Top-k Queries	2015	VLDB