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CrowdDB: Query Processing with the VLDB Crowd

Summary: CrowdDB: a hybrid DB using crowdsourcing to answer queries with missing data and fuzzy semantics. SQL-based querying and data modeling with compilation/optimization; operators expose UI to collect and cleanse human input; supports MTurk and mobile crowds. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10398
Venue
VLDB
Year
2011
Pagerank
9.7021022e-05
Overall Rank
1,810 | 87.59%
DOI
10.14778/3402755.3402777

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{feng_vldb11,
        title = {{CrowdDB: Query Processing with the VLDB Crowd}},
        author = {Feng, Amber and Franklin, Michael and Kossmann, Donald and Kraska, Tim and Madden, Samuel and Ramesh, Sukriti and Wang, Andrew and Xin, Reynold},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {12},
        pages = {1387--1390},
        doi = {10.14778/3402755.3402777},
        url = {https://doi.org/10.14778/3402755.3402777},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
90 CrowdDB: Answering Queries with Crowdsourcing 2011 SIGMOD 0.00034951786
2,165 Demonstration of Qurk: A Query Processor for Human Operators 2011 SIGMOD 9.0507521e-05
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