Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing

With the increased interest in machine learning and big data problems, the need for large amounts of labelled data has also grown. However, it is often infeasible to get experts to label all of this data, which leads many practitioners to crowdsourcing solutions. In this paper, we present new techni...

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Bibliographic Details

Published in:	2020 International SAUPEC/RobMech/PRASA Conference pp. 1 - 6
Main Authors:	Burke, Pierce, Klein, Richard
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.01.2020
Subjects:	Bayes methods Bayesian Inference Classification algorithms Consensus Costs Crowdsourcing Inference algorithms Inter-rater Agreement Iterative algorithms Machine learning Maximum Likelihood
Online Access:	Get full text
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