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Crowdsourcing Analytics with CrowdCur

Summary: CrowdCur enables crowdsourcing analytics for admins, requesters, and workers via worker curation and completion-based task curation. OLAP-style analytics by worker or task type; admins tune, requesters compare platforms, workers locate tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5586
Venue
SIGMOD
Year
2018
Pagerank
5.093636e-05
Overall Rank
11,925 | 18.19%
DOI
10.1145/3183713.3193563

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Authors

BibTeX Citation

@inproceedings{esfandiari_sigmod18,
        title = {{Crowdsourcing Analytics with CrowdCur}},
        author = {Esfandiari, Mohammadreza and Patel, Kavan Bharat and Amer-Yahia, Sihem and Roy, Senjuti Basu},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3193563},
        url = {https://dl.acm.org/doi/10.1145/3183713.3193563},
        year = {2018}
}

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

Rank Cited Paper Year Venue Pagerank
2,136 Combining User Interaction, Speculative Query Execution and Sampling in the DICE System 2014 VLDB 9.1126926e-05
10,029 Human Factors in Crowdsourcing 2016 VLDB 5.1741314e-05
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