Studying crowdsourcing using machine learning and optimisation-based approaches

Moayedikia, Alireza 2018, Studying crowdsourcing using machine learning and optimisation-based approaches, Ph.D thesis, Department of Information Systems & Business Analytics, Deakin University.

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Title Studying crowdsourcing using machine learning and optimisation-based approaches
Author Moayedikia, Alireza
Institution Deakin University
School Department of Information Systems & Business Analytics
Faculty Faculty of Business & Law
Degree type Research doctorate
Degree name Ph.D
Thesis advisor Yeoh, WilliamORCID iD for Yeoh, William orcid.org/0000-0002-2964-4518
Date submitted 2018-08-01
Summary This study addressed the challenge of optimising cost and improving accuracy for microtask-crowdsourcing platforms. The research introduced a new method that is able to optimise task assignment, reduce payments to spammers and avoid collecting their answers.
Language eng
Field of Research 080605 Decision Support and Group Support Systems
Socio Economic Objective 890202 Application Tools and System Utilities
Description of original 214 p.
Restricted until 2019-08-06
Copyright notice ┬ęThe author
Persistent URL http://hdl.handle.net/10536/DRO/DU:30112388

Document type: Thesis
Collection: Higher degree theses (citation only)
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Created: Mon, 13 Aug 2018, 13:25:12 EST by Bayne Christine

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