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dc.contributor.authorSoares, Felipept_BR
dc.contributor.authorRebechi, Rozane Rodriguespt_BR
dc.contributor.authorStevenson, Markpt_BR
dc.date.accessioned2021-03-12T04:19:49Zpt_BR
dc.date.issued2020pt_BR
dc.identifier.issn2234-0742pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/218665pt_BR
dc.description.abstractScientific research is mostly published in English, regardless of the researcher’s nationality. However, this growing practice impairs or hinders the comprehension of professionals who depend on the results of these studies to provide adequate care for their patients. We suggest that machine translation (MT) can be used as a way of providing useful translation for biomedical articles, even though the translation itself may not be fluent. To tackle possible mistranslation that can harm a patient, we resort to crowd-sourced validation of translations. We developed a prototype of MT validation and edition, where users can vote for that translation as valid, or suggest modifications (i.e., post-editing the MT). A glossary match system is also included, aiming at terminology consistency.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofGenomics & Informatics. Seoul, Korea. Vol. 18, n. 2 (jun. 2020), p. 52-58pt_BR
dc.rightsOpen Accessen
dc.subjectCrowdsourcingen
dc.subjectTradução automáticapt_BR
dc.subjectLinguisticsen
dc.subjectBiomedicinapt_BR
dc.subjectTerminologiapt_BR
dc.subjectMachine translationen
dc.subjectLinguísticapt_BR
dc.subjectMedical informatics applicationsen
dc.subjectPubMeden
dc.titleSciBabel : a system for crowd-sourced validation of automatic translations of scientific textspt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001122811pt_BR
dc.type.originEstrangeiropt_BR


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