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UPI: A Primary Index for Uncertain Databases

Summary: UPI is a primary index for uncertain databases, clustering by uncertain attributes and duplicating tuples per possible value. It adds a Cutoff Index to cap low-probability data and uses buffered, batched updates with cost models, delivering up to 100x faster uncertain queries than baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10302
Venue
VLDB
Year
2010
Pagerank
5.6004812e-05
Overall Rank
7,553 | 48.19%
DOI
10.14778/1920841.1920922

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{kimura_vldb10,
        title = {{UPI: A Primary Index for Uncertain Databases}},
        author = {Kimura, Hideaki and Madden, Samuel and Zdonik, Stanley B.},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {630--641},
        doi = {10.14778/1920841.1920922},
        url = {https://doi.org/10.14778/1920841.1920922},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
8,585 Probabilistic Management of OCR Data using an RDBMS 2012 VLDB 5.4075213e-05
12,103 Indexing Metric Uncertain Data for Range Queries 2015 SIGMOD 5.093636e-05
12,104 Supporting Data Uncertainty in Array Databases 2015 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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