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Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations

Summary: Addresses conditioned aggregates over uncertain streams, where exact answer distributions are generally intractable. Introduces an approximation framework with error metrics and representations, plus fast deterministic/randomized streaming algorithms with bounded-error guarantees. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h42d6a1b54561fb46
Venue
VLDB
Year
2010
Pagerank
4.9793485e-05
Overall Rank
12,758 | 14.23%
DOI
10.14778/1920841.1921003

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Authors

BibTeX Citation

@article{tran_vldb10,
        title = {{Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations}},
        author = {Tran, Thanh T. L. and McGregor, Andrew and Diao, Yanlei and Peng, Liping and Liu, Anna},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {1302--1313},
        doi = {10.14778/1920841.1921003},
        url = {https://doi.org/10.14778/1920841.1921003},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
7,863 Optimizing Probabilistic Query Processing on Continuous Uncertain Data 2011 VLDB 5.4367962e-05
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