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Minimizing Efforts in Validating Crowd Answers

Summary: Proposes a probabilistic model to identify the most beneficial validation questions in crowdsourced answers, enhancing correctness and flagging faulty workers. Demonstrates up to 50% expert savings and near-perfect correctness after only ~20% of questions are validated. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5013
Venue
SIGMOD
Year
2015
Pagerank
5.4454221e-05
Overall Rank
8,351 | 42.71%
DOI
10.1145/2723372.2723731

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{hung_sigmod15,
        title = {{Minimizing Efforts in Validating Crowd Answers}},
        author = {Hung, Nguyen Quoc Viet and Thang, Duong Chi and Weidlich, Matthias and Aberer, Karl},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2723731},
        url = {https://dl.acm.org/doi/10.1145/2723372.2723731},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,281 Cleaning Crowdsourced Labels Using Oracles for Statistical Classification 2019 VLDB 7.5706653e-05
7,628 User Guidance for Efficient Fact Checking 2019 VLDB 5.5798467e-05
11,975 Staging User Feedback toward Rapid Conflict Resolution in Data Fusion 2017 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

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