Tailoring Data Source Distributions for Fairness-aware Data Integration
Summary: Tailors data-source mixes to satisfy fairness-based distributions under cost constraints. Known distributions with equal costs yield optimal results; for unknowns or unequal costs, use approximations with exploration–exploitation and validation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Fatemeh Nargesian (University of Rochester)
- 2. Abolfazl Asudeh (University of Illinois Chicago)
- 3. H. V. Jagadish (University of Michigan)
BibTeX Citation
@article{nargesian_vldb21,
title = {{Tailoring Data Source Distributions for Fairness-aware Data Integration}},
author = {Nargesian, Fatemeh and Asudeh, Abolfazl and Jagadish, H. V.},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {11},
pages = {2519--2532},
doi = {10.14778/3476249.3476299},
url = {https://doi.org/10.14778/3476249.3476299},
year = {2021}
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