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Iterative Learning for K-Approval Votes in Crowdsourcing Systems
2021
Applied Sciences
Crowdsourcing systems have emerged as cornerstones to collect large amounts of qualified data in various human-powered problems with a relatively low budget. In eliciting the wisdom of crowds, many web-based crowdsourcing platforms have encouraged workers to select top-K alternatives rather than just one choice, which is called "K-approval voting". This kind of setting has the advantage of inducing workers to make fewer mistakes when they respond to target tasks. However, there is not much work
doi:10.3390/app11020630
fatcat:3hvhsxrky5cynnkt4hgek5jgu4