Perspectives on Crowdsourcing Annotations for Natural Language Processing

dc.contributor.authorWANG, Aoboen_US
dc.contributor.authorHOANG, Cong Duy Vuen_US
dc.contributor.authorKAN, Min-Yenen_US
dc.date.accessioned2010-07-27T01:46:23Zen_US
dc.date.accessioned2017-01-23T07:00:13Z
dc.date.available2010-07-27T01:46:23Zen_US
dc.date.available2017-01-23T07:00:13Z
dc.date.issued2010-07-27T01:46:23Zen_US
dc.description.abstractCrowdsourcing has emerged as a new method for obtaining annotations for training models for machine learning. While many variants of this process exist, they largely differ in their method of motivating subjects to contribute and the scale of their applications. To date, however, there has yet to be a study that helps a practitioner to decide what form an annotation application should take to best reach its objectives within the constraints of a project. We first provide a faceted analysis of existing crowdsourcing annotation applications. We then use our analysis to discuss our recommendations on how practitioners can take advantage of crowdsourcing and discuss our view on potential opportunities in this area.en_US
dc.format.extent218976 bytesen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.urihttps://dl.comp.nus.edu.sg/xmlui/handle/1900.100/3266en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTRB7/10en_US
dc.titlePerspectives on Crowdsourcing Annotations for Natural Language Processingen_US
dc.typeTechnical Reporten_US
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