Aggregating crowdsourced binary ratings

Author:

Dalvi Nilesh1,Dasgupta Anirban2,Kumar Ravi3,Rastogi Vibhor3

Affiliation:

1. Facebook, Menlo Park, CA, USA

2. Yahoo! Labs, Sunnyvale, CA, USA

3. Google, Mountain View, CA, USA

Publisher

ACM Press

Reference19 articles.

1. S. Boyd and J. Dattorro. Alternating projections, 2003. www.stanford.edu/class/ee392o/altproj.pdf.

2. B. Carpenter. A hierarchical Bayesian model of crowdsourced relevance coding. In Prof. 12th TREC, 2011.

3. A. Dawid and A. Skene. Maximum likelihood estimation of observer error-rates using the EM algorithm. Applied Statistics, pages 20--28, 1979.

4. O. Dekel and O. Shamir. Vox populi: Collecting high-quality labels from a crowd. In Proc. 22nd COLT, 2009.

5. A. Ghosh, S. Kale, and R. P. McAfee. Who moderates the moderators?: Crowdsourcing abuse detection in user-generated content. In Proc. 12th EC, pages 167--176, 2011.

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