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)
Incoming Non-self Citations Over Time
Authors
- 1. Nguyen Quoc Viet Hung (EPFL)
- 2. Duong Chi Thang (EPFL)
- 3. Matthias Weidlich (Imperial College London)
- 4. Karl Aberer (EPFL)
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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