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dc.contributor.authorMedina Herrera, Salvador
dc.contributor.authorTurmo Borras, Jorge
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Intel·ligència Artificial
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2021-05-11T09:12:55Z
dc.date.available2021-05-11T09:12:55Z
dc.date.issued2020
dc.identifier.citationMedina, S.; Turmo, J. TALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations. A: Iberian Languages Evaluation Forum. "Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020): co-located with 36th Conference of the Spanish Society for Natural Language Processing (SEPLN 2020): Málaga, Spain, September 23th, 2020". CEUR-WS.org, 2020, p. 85-93. ISBN 1613-0073.
dc.identifier.isbn1613-0073
dc.identifier.urihttp://hdl.handle.net/2117/345413
dc.description.abstractThis article describes the model presented by the TALP Team to IberLEF’s eHealth Knowledge Discovery 2020 shared task[1]. The model iterates over the idea of using a single model for simultaneously identify key-phrases and their relationships. Taking into account the new transfer-learning sub-task presented for 2020’s edition of eHealthKD, our model does not rely on any domain-specific knowledge nor handcrafted features. Our model was competitive in all four sub-tasks, ranking in 2nd, 3rd, 4th and 1st position respectively.
dc.description.sponsorshipThis contribution has been partially funded by the Spanish Ministry of Economy (MINECO) and the European Union (TIN2016-77820-C3-3-R and AEI/ FEDER,UE).
dc.format.extent9 p.
dc.language.isoeng
dc.publisherCEUR-WS.org
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
dc.subject.lcshComputational linguistics
dc.subject.lcshNeural networks (Computer science)
dc.subject.otherNERC
dc.subject.otherRelation extraction
dc.subject.othereHealth NLP
dc.subject.otherContextual embeddings
dc.titleTALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations
dc.typeConference report
dc.subject.lemacLingüística computacional
dc.subject.lemacXarxes neuronals (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ceur-ws.org/Vol-2664/eHealth-KD_paper1.pdf
dc.rights.accessOpen Access
local.identifier.drac31275062
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/TIN2016-77820-C3-3-R
local.citation.authorMedina, S.; Turmo, J.
local.citation.contributorIberian Languages Evaluation Forum
local.citation.publicationNameProceedings of the Iberian Languages Evaluation Forum (IberLEF 2020): co-located with 36th Conference of the Spanish Society for Natural Language Processing (SEPLN 2020): Málaga, Spain, September 23th, 2020
local.citation.startingPage85
local.citation.endingPage93


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