Models and Mechanisms for Spatial Data Fairness

Summary: Introduce spatial data fairness, formalizing fairness for location data and spatial queries, and propose fair polynomials as a novel building block. Present two mechanisms (distance- and zone-based) that enforce individual spatial fairness with minimal utility loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13026
Venue: VLDB
Year: 2023
Pagerank: 4.7180617e-05
Overall Rank: 7,490 | 47.90%
DOI: 10.14778/3565816.3565820

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,317	Highly-Efficient Large-Scale k-means with Individual Fairness	2026	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

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

Rank	Cited Paper	Year	Venue	Pagerank

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