Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/60755
Título: | Next generation community assessment of biomedical entity recognition web servers: metrics, performance, interoperability aspects of BeCalm |
Autor(es): | Pérez-Pérez, Martin Pérez-Rodríguez, Gael Blanco-Míguez, Aitor Fdez-Riverola, Florentino Valencia, Alfonso Krallinger, Martin Lourenço, Anália |
Palavras-chave: | Named entity recognition Shared task REST-API TIPS BeCalm metaserver Patent mining Annotation server Continuous evaluation BioCreative Text mining |
Data: | Dez-2019 |
Editora: | SpringerOpen |
Revista: | Journal of Cheminformatics |
Citação: | Pérez-Pérez, Martin; Pérez-Rodríguez, Gael; Blanco-Míguez, Aitor; Fdez-Riverola, Florentino; Valencia, Alfonso; Krallinger, Martin; Lourenço, Anália, Next generation community assessment of biomedical entity recognition web servers: metrics, performance, interoperability aspects of BeCalm. Journal of Cheminformatics, 11(42), 2019 |
Resumo(s): | Shared tasks and community challenges represent key instruments to promote research, collaboration and determine the state of the art of biomedical and chemical text mining technologies. Traditionally, such tasks relied on the comparison of automatically generated results against a so-called Gold Standard dataset of manually labelled textual data, regardless of efficiency and robustness of the underlying implementations. Due to the rapid growth of unstructured data collections, including patent databases and particularly the scientific literature, there is a pressing need to generate, assess and expose robust big data text mining solutions to semantically enrich documents in real time. To address this pressing need, a novel track called ``Technical interoperability and performance of annotation servers'' was launched under the umbrella of the BioCreative text mining evaluation effort. The aim of this track was to enable the continuous assessment of technical aspects of text annotation web servers, specifically of online biomedical named entity recognition systems of interest for medicinal chemistry applications. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/60755 |
DOI: | 10.1186/s13321-019-0363-6 |
ISSN: | 1758-2946 |
Versão da editora: | https://jcheminf.biomedcentral.com/ |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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document_51783_1.pdf | 2,22 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons