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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)

Paper ID
9807
Venue
VLDB
Year
2007
Pagerank
5.093636e-05
Overall Rank
12,671 | 13.07%
DOI
10.1145/1325851.1325924

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Authors

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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