Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing
Summary: Randomized algorithms enable efficient deployment of entity-resolution methods for wide-area, federated aggregate queries. They reconcile duplicates and inconsistencies across distributed sources without shipping raw data to a central coordinator, yielding accurate, approximate aggregates. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Fei Xu (University of Florida)
- 2. Christopher Jermaine (University of Florida)
BibTeX Citation
@article{xu_vldb07,
title = {{Randomized Algorithms for Data Reconciliation in Wide Area Aggregate Query Processing}},
author = {Xu, Fei and Jermaine, Christopher},
journal = {PVLDB},
series = {{VLDB} '07},
pages = {639--650},
doi = {10.1145/1325851.1325924},
url = {https://doi.org/10.1145/1325851.1325924},
year = {2007}
}
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