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A Demonstration of DBWipes: Clean as You Query

Summary: DBWipes interactively cleans aggregate-query errors by ranking influential input subsets rather than exposing entire collections. Human-readable predicates explain each subset’s contribution, enabling precise anomaly diagnosis in real campaign and sensor data. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10617
Venue
VLDB
Year
2012
Pagerank
5.8609765e-05
Overall Rank
6,499 | 55.42%
DOI
10.14778/2367502.2367558

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{wu_vldb12,
        title = {{A Demonstration of DBWipes: Clean as You Query}},
        author = {Wu, Eugene and Madden, Samuel and Stonebraker, Michael},
        journal = {PVLDB},
        series = {{VLDB} '12},
        volume = {5},
        number = {12},
        pages = {1894--1897},
        doi = {10.14778/2367502.2367558},
        url = {https://doi.org/10.14778/2367502.2367558},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
1,768 Tuplex: Data Science in Python at Native Code Speed 2021 SIGMOD 9.8041636e-05
1,798 SMOKE: Fine-grained Lineage at Interactive Speed 2018 VLDB 9.7361937e-05
4,890 Descriptive and Prescriptive Data Cleaning 2014 SIGMOD 6.4590072e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

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