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Incentivize crowd labeling under budget constraint
2015
2015 IEEE Conference on Computer Communications (INFOCOM)
Crowdsourcing systems allocate tasks to a group of workers over the Internet, which have become an effective paradigm for human-powered problem solving such as image classification, optical character recognition and proofreading. In this paper, we focus on incentivizing crowd workers to label a set of binary tasks under strict budget constraint. We properly profile the tasks' difficulty levels and workers' quality in crowdsourcing systems, where the collected labels are aggregated with
doi:10.1109/infocom.2015.7218674
dblp:conf/infocom/ZhangWTGW15
fatcat:i4wvgqcbdjditkk5ohaxrdd2re