Supporting Dynamic Construction of Datasets with Annotator Suggestions

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dc.contributor.authorPark, Jeongeonko
dc.contributor.authorKo, Eunyoungko
dc.contributor.authorHan, Donghoonko
dc.contributor.authorYim, Jinyeongko
dc.contributor.authorKim, Juhoko
dc.date.accessioned2021-11-30T06:49:25Z-
dc.date.available2021-11-30T06:49:25Z-
dc.date.created2021-11-29-
dc.date.issued2021-11-17-
dc.identifier.citationThe 9th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021-
dc.identifier.urihttp://hdl.handle.net/10203/289697-
dc.description.abstractThe construction process for machine learning datasets is costly for experts as it requires going through multiple iterations to build a label set and communicating and resolving issues with annotators. To make the process more efficient for experts, we propose DynamicLabels, which allows experts to refine the dataset structure with label set suggestions collected by the annotators.-
dc.languageEnglish-
dc.publisherAAAI-
dc.titleSupporting Dynamic Construction of Datasets with Annotator Suggestions-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameThe 9th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationVirtual-
dc.contributor.localauthorKim, Juho-
dc.contributor.nonIdAuthorPark, Jeongeon-
dc.contributor.nonIdAuthorKo, Eunyoung-
dc.contributor.nonIdAuthorHan, Donghoon-
dc.contributor.nonIdAuthorYim, Jinyeong-
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CS-Conference Papers(학술회의논문)
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