Database Paper Browser

Back to papers

Fairness in Preference Queries: Social Choice Theories Meet Data Management

Summary: Applies social choice methods to preference queries at scale, comparing elicitation models and aggregators (Kemeny, Borda, STV/IRV) and outputs (full orders, top‑k). Surveys fairness fixes—input/output repairs and metrics—and pinpoints scalability, elicitation‑aware fairness, and algorithmic/complexity gaps for future DB research. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13623
Venue
VLDB
Year
2024
Pagerank
4.3648789e-05
Overall Rank
9,248 | 35.73%
DOI
10.14778/3685800.3685841

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,223 On Fair Epsilon Net and Geometric Hitting Set 2026 VLDB 4.1905499e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
3,804 Group Recommendation: Semantics and Efficiency 2009 VLDB 6.7487709e-05
6,422 From Group Recommendations to Group Formation 2015 SIGMOD 5.0621949e-05
7,425 Rank Aggregation with Proportionate Fairness 2022 SIGMOD 4.7292787e-05
8,978 Satisfying Complex Top-k Fairness Constraints by Preference Substitutions 2023 VLDB 4.4144821e-05
11,220 Equitable Top-k Results for Long Tail Data 2023 SIGMOD 4.1905499e-05
Previous Page 1 / 1 Next

Semantically Similar Papers