Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Aitor Gonzalez-Agirre"'
Autor:
Marta Villegas, Aitor Gonzalez-Agirre, Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Casimiro Pio Carrino, David Pérez-Fernández, Felipe Soares, Pablo Serrano, Miguel Pedrera, Noelia García, Alfonso Valencia
Publikováno v:
Computer Methods and Programs in Biomedicine Update, Vol 3, Iss , Pp 100089- (2023)
Background:: In December 2020, the COVID-19 disease was confirmed in 1,665,775 patients and caused 45,784 deaths in Spain. At that time, health decision support systems were identified as crucial against the pandemic. Methods:: This study applies Dee
Externí odkaz:
https://doaj.org/article/c1088fb40d504afba9e532b9339bc70c
Autor:
Aitor Gonzalez-Agirre, German Rigau
Publikováno v:
Linguamática, Vol 5, Iss 1 (2013)
El uso de recursos semánticos de amplia cobertura y dominio general se ha convertido en una práctica común y a menudo necesaria para los sistemas actuales de Procesamiento del Lenguaje Natural (PLN). WordNet es, con mucho, el recurso semántico m
Externí odkaz:
https://doaj.org/article/6fcf10a3274740fea8cbaf78b7bd5c91
Autor:
Casimiro Pio Carrino, Joan Llop, Marc Pàmies, Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Joaquín Silveira-Ocampo, Alfonso Valencia, Aitor Gonzalez-Agirre, Marta Villegas
This work presents the first large-scale biomedical Spanish language models trained from scratch, using large biomedical corpora consisting of a total of 1.1B tokens and an EHR corpus of 95M tokens. We compared them against general-domain and other d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8a93220592539856ae790aa08eb70e0
https://hdl.handle.net/2117/374590
https://hdl.handle.net/2117/374590
Autor:
Marta Villegas, Aitor Gonzalez-Agirre, Noelia Garcia, Felipe Soares, Casimiro Pio Carrino, David Pérez Fernández, Pablo Serrano, Asier Gutiérrez-Fandiño, Alfonso Valencia, Jordi Armengol-Estapé, Miguel Pedrera
Publikováno v:
Computer methods and programs in biomedicine update. 3
BackgroundThe propagation of COVID-19 in Spain prompted the declaration of the state of alarm on March 14, 2020. On 2 December 2020, the infection had been confirmed in 1,665,775 patients and caused 45,784 deaths. This unprecedented health crisis cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30f40b9324c10de5a345989cab556aa7
https://pubmed.ncbi.nlm.nih.gov/36593771
https://pubmed.ncbi.nlm.nih.gov/36593771
Autor:
Aitor Gonzalez-Agirre, Carlos Rodriguez-Penagos, Carme Armentano-Oller, Casimiro Pio Carrino, Jordi Armengol-Estapé, Marta Villegas, Maite Melero, Ona de Gibert Bonet
Publikováno v:
ACL/IJCNLP (Findings)
Multilingual language models have been a crucial breakthrough as they considerably reduce the need of data for under-resourced languages. Nevertheless, the superiority of language-specific models has already been proven for languages having access to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::575ed20002b3f096d73040639ffe7fa0
https://doi.org/10.18653/v1/2021.findings-acl.437
https://doi.org/10.18653/v1/2021.findings-acl.437
Autor:
Montse Maritxalar, Larraitz Uria, Eneko Agirre, Aitor Gonzalez-Agirre, Iñigo Lopez-Gazpio, German Rigau
Publikováno v:
Recercat. Dipósit de la Recerca de Catalunya
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User acceptance of artificial intelligence agents might depend on their ability to explain their reasoning, which requires adding an interpretability layer that fa- cilitates users to understand their behavior. This paper focuses on adding an in- ter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b7c7d8c6337120211761dbd802240e9
https://doi.org/10.1016/j.knosys.2016.12.013
https://doi.org/10.1016/j.knosys.2016.12.013
Autor:
Montserrat Moreno Marimon, Marta Villegas, Martin Krallinger, Ander Intxaurrondo, Aitor Gonzalez-Agirre, Obdulia Rabal
Publikováno v:
BioNLP-OST@EMNLP-IJNCLP
One of the biomedical entity types of relevance for medicine or biosciences are chemical compounds and drugs. The correct detection these entities is critical for other text mining applications building on them, such as adverse drug-reaction detectio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f830c5d91578c129ac5103c9142f309d
https://doi.org/10.18653/v1/d19-5701
https://doi.org/10.18653/v1/d19-5701
Autor:
Felipe Soares, Aitor Gonzalez-Agirre, Marta Villegas, Martin Krallinger, Jordi Armengol-Estapé
Publikováno v:
Proceedings of the 2nd Clinical Natural Language Processing Workshop.
Word embeddings are representations of words in a dense vector space. Although they are not recent phenomena in Natural Language Processing (NLP), they have gained momentum after the recent developments of neural methods and Word2Vec. Regarding their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7261b3aa013aa38fe8002bc575c48f87
https://doi.org/10.18653/v1/w19-1916
https://doi.org/10.18653/v1/w19-1916
Publikováno v:
Journal of the Association for Information Science and Technology. 67:1624-1638
We introduce a new problem, identifying the type of relation that holds between a pair of similar items in a digital library. Being able to provide a reason why items are similar has applications in recommendation, personalization, and search. We inv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b43f5984f53c4e9a99249dcd5f1fe8c
https://doi.org/10.1002/asi.23482
https://doi.org/10.1002/asi.23482
Autor:
Larraitz Uria, Montse Maritxalar, Iñigo Lopez-Gazpio, German Rigau, Eneko Agirre, Aitor Gonzalez-Agirre
Publikováno v:
SemEval@NAACL-HLT
In Semantic Textual Similarity, systems rate the degree of semantic equivalence on a graded scale from 0 to 5, with 5 being the most similar. For the English subtask, we present a system which relies on several resources for token-to-token and phrase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c8bbd712253389b8d07fe6a15fb0535
https://doi.org/10.18653/v1/s15-2032
https://doi.org/10.18653/v1/s15-2032