Automatically producing semantically tagged bilingual terminologies

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Vivaldi, J. (Jorge), 1952-
• dc.contributor.author Rodríguez, Horacio
• dc.date.accessioned 2022-05-18T12:09:39Z
• dc.date.available 2022-05-18T12:09:39Z
• dc.date.issued 2022
• dc.description.abstract Even though many NLP resources and tools claim to be domain independent, their application to specifc tasks is restricted to some specifc domain, otherwise their performance degrade notably. As the accuracy of NLP resources drops heavily when applied in environments diferent from which they were built a tuning to the new environment is needed. This paper proposes a method for automatically compile terminologies from potentially any domain. The proposed method takes as reference the set of domains defned by Magnini, the Multilingual Central Repository (a resource based on WordNet 3.0) together with DBpedia, an open knowledge source that had proven to be reliable for restricted domains. Using the method described in this article, we have produced a big set of reliable terminologies for 164 domains and 2 languages totalling 635,527 terms. The proposed method has been applied to English and Spanish languages but it is potentially applicable to any language that has its own a DBpedia evolved enough. The obtained results have been intensively evaluated in several ways.
• dc.description.sponsorship The author Jorge Vivaldi was partially funded by the public supported project TERMMED (FFI2017-88100-P, MINECO). The author Horacio Rodríguez was partially supported by the public funded project GRAPHMED (TIN2016-77820-C3-3R).
• dc.format.mimetype application/pdf
• dc.identifier.citation Vivaldi J, Rodríguez H. Automatically producing semantically tagged bilingual terminologies. SN Comput Sci. 2022;3:76. DOI: 10.1007/s42979-021-00952-7
• dc.identifier.doi http://dx.doi.org/10.1007/s42979-021-00952-7
• dc.identifier.issn 2662-995X
• dc.identifier.uri http://hdl.handle.net/10230/53145
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/FFI2017-881
• dc.rights © The Author(s) 2021 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Multi-domain term collection and bilingual terminologies
• dc.subject.keyword MCR-based terminologies
• dc.title Automatically producing semantically tagged bilingual terminologies
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion