Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Alejandro Piad-Morffis"'
Publikováno v:
GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología, Vol 2, Iss 3 (2022)
El trabajo presenta una alternativa para identificar idiomas en Twitter sin que sea necesario utilizar conjuntos de entrenamiento o información agregada. En dicha alternativa se utilizan técnicas basadas en los algoritmos de reconocimiento de trigr
Externí odkaz:
https://doaj.org/article/599a76fc039d42f899e455cb9817498b
Publikováno v:
GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología, Vol 2, Iss 3, Pp 35-45 (2014)
Resumen El trabajo presenta una alternativa para identificar idiomas en Twitter sin que sea necesario utilizar conjuntos de entrenamiento o información agregada. En dicha alternativa se utilizan técnicas basadas en los algoritmos de reconocimien
Externí odkaz:
https://doaj.org/article/c1cd49100db74c61870a8c2e0d7bfba6
Autor:
Houcemeddine Turki, Dennis Priskorn, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha, Alejandro Piad-Morffis
Named Entity Recognition (NER) is currently a key technique is knowledge engineering, particularly in the context of biomedical informatics. In this context, Wikidata has been used as a Knowledge Graph to drive named entity recognition for various ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::492443d0ac0ee97e1019e5a35922cdbf
Autor:
Houcemeddine Turki, Mohamed Ali Hadj Taieb, Alejandro Piad-Morffis, Mohamed Ben Aouicha, René Fabrice Bile
Semantic text annotations have been a key factor for supporting computer applications ranging from knowledge graph construction to biomedical question answering. In this systematic review, we provide an analysis of the data models that have been appl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd18f0e9ab4aca5990af8db5b8226ec4
https://zenodo.org/record/6421057
https://zenodo.org/record/6421057
Exploiting discourse structure of traditional digital media to enhance automatic fake news detection
Autor:
Estela Saquete, Patricio Martínez-Barco, Alba Bonet-Jover, Alejandro Piad-Morffis, Miguel A. García-Cumbreras
Publikováno v:
Expert Systems with Applications
This paper presents a novel architecture for dealing with Automatic Fake News detection. The architecture factors in the discourse structure of news in traditional digital media and is based on two premises. First, fake news tends to mix true and fal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cd893d3792f20e64965020cd2fb858d
https://hdl.handle.net/10045/112843
https://hdl.handle.net/10045/112843
Autor:
Yoan Gutiérrez, Suilan Estevez-Velarde, Rafael Muñoz-Guillena, Andrés Montoyo, Alejandro Piad-Morffis, Yudivián Almeida Cruz, Hian Cañizares-Diaz
Publikováno v:
RANLP
This paper presents an active learning approach that aims to reduce the human effort required during the annotation of natural language corpora composed of entities and semantic relations. Our approach assists human annotators by intelligently select
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc9d218abe7c8d926722dd2e9217c9e9
https://doi.org/10.26615/978-954-452-072-4_026
https://doi.org/10.26615/978-954-452-072-4_026
Autor:
Yudivián Almeida-Cruz, Rafael Muñoz, Alejandro Piad-Morffis, Yoan Gutiérrez, Ernesto Luis Estevanell-Valladares, Andrés Montoyo, Suilan Estevez-Velarde
Publikováno v:
NLP4COVID@EMNLP
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
RANLP
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
RANLP
This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic. In this research, a general-purpose semantic model is used to double annotate a batch of 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::511d3b73787fd64717edffe2a8dbf93f
https://hdl.handle.net/10045/110386
https://hdl.handle.net/10045/110386
Autor:
Araujo R, C. Fonte, Vidal M, Valdes Je, Fonte P, Patricia Lorenzo-Luaces, Pria MdC, Yudivián Almeida-Cruz, C Sebrango, Morales W, Pedro Mas, Suilan Estevez-Velarde, Antoni Torres, Noriega, Corral A, Crespo M, Baldoquin W, Alejandro Piad-Morffis, N. Pérez, Guinovart R, Lizet Sánchez, Agustin Lage
Publikováno v:
SSRN Electronic Journal.
Background. There is a gap for the effective use of mathematical models for real-time decision-making. We aimed to illustrate with the Cuban experience to control the COVID-19, how mathematical models can be put in place to answer key decision-makers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6336e8984087c4f8b21d87c1c21ffe8
https://doi.org/10.2139/ssrn.3629271
https://doi.org/10.2139/ssrn.3629271
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
Journal of Biomedical Informatics
Universidad de Alicante (UA)
Journal of Biomedical Informatics
Graphical abstract
Highlights • An annotation model to capture broad sentence-level semantics is defined. • A manually annotated corpus of 1045 Spanish health sentences is presented. • A definition of a knowledge discovery task based on th
Highlights • An annotation model to capture broad sentence-level semantics is defined. • A manually annotated corpus of 1045 Spanish health sentences is presented. • A definition of a knowledge discovery task based on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfa969dfa61e327c039d93c977f25bf8
http://hdl.handle.net/10045/108381
http://hdl.handle.net/10045/108381
Autor:
Rafael Muñoz-Guillena, Andrés Montoyo, Alejandro Piad-Morffis, Yudivián Almeida Cruz, Yoan Gutiérrez, Suilan Estevez-Velarde
Publikováno v:
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
COLING (Demonstrations)
Universidad de Alicante (UA)
COLING (Demonstrations)
This paper introduces a web demo that showcases the main characteristics of the AutoGOAL framework. AutoGOAL is a framework in Python for automatically finding the best way to solve a given task. It has been designed mainly for automatic machine lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8082100bae62c8cafcdcb68b4e85a022
http://hdl.handle.net/10045/110741
http://hdl.handle.net/10045/110741