Community-based bayesian aggregation models for crowdsourcing

Abstract

This paper addresses the problem of extracting accurate labels from crowdsourced datasets, a key challenge in crowdsourcing. Prior work has focused on modeling the reliability of individual workers, for instance, by way of confusion matrices, and using these latent traits to estimate the true labels more accurately. However, this strategy becomes… (More)
DOI: 10.1145/2566486.2567989

9 Figures and Tables

Topics

Statistics

0204020142015201620172018
Citations per Year

130 Citations

Semantic Scholar estimates that this publication has 130 citations based on the available data.

See our FAQ for additional information.

  • Presentations referencing similar topics