POS-tags features for Protein-Protein Interaction Extraction from Biomedical Articles

Pedro Shiguihara-Juarez, Nils Murrugarra-Llerena, Alneu De Andrade Lopes

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Protein-Protein Interaction (PPI) extraction from biomedical articles consists on extracting sentences were two or more proteins interact. Traditional articles tackle this problem creating more sophisticated classifiers. In contrast to them, we focus on discriminative features that can be exploited by traditional classifiers. Our method exploits information from POS-tags features and are combined with a bag-of-words approach. We used five standard corpora of PPI: Aimed, Bioinfer, HPRD50, IEPA and LLL. Our method is simple and achieves high results compared with other approaches. We achieve an improvement of 11% with our best competitor.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538654903
DOI
EstadoPublicada - 6 nov. 2018
Publicado de forma externa
Evento25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018 - Lima, Perú
Duración: 8 ago. 201810 ago. 2018

Serie de la publicación

NombreProceedings of the 2018 IEEE 25th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018

Conferencia

Conferencia25th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2018
País/TerritorioPerú
CiudadLima
Período8/08/1810/08/18

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