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dc.contributor.authorBeñaran-Muñoz, I. 
dc.contributor.authorHernández, J.
dc.contributor.authorPérez, A. 
dc.date.accessioned2023-10-10T14:10:37Z
dc.date.available2023-10-10T14:10:37Z
dc.date.issued2022
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1662
dc.description.abstractThe use of crowdsourcing for annotating data has become a popular and cheap alternative to expert labelling. As a consequence, an aggregation task is required to combine the different labels provided and agree on a single one per example. Most aggregation techniques, including the simple and robust majority voting—to select the label with the largest number of votes—disregard the descriptive information provided by the explanatory variable. In this paper, we propose domain-aware voting, an extension of majority voting which incorporates the descriptive variable and the rest of the instances of the dataset for aggregating the label of every instance. The experimental results with simulated and real-world crowdsourced data suggest that domain-aware voting is a competitive alternative to majority voting, especially when a part of the dataset is unlabelled. We elaborate on practical criteria for the use of domain-aware voting.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectCrowdsourcing, Label aggregationen_US
dc.titleOn the use of the descriptive variable for enhancing the aggregation of crowdsourced labelsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doihttps://doi.org/10.1007/s10115-022-01743-zen_US
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s10115-022-01743-zen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//SEV-2017-0718en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno Vasco/ELKARTEKen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2022-2025en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titleKnowledge and Information Systemsen_US
dc.volume.number65en_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España