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A Knowledge-Based Weighted KNN for Detecting Irony in Twitter

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A Knowledge-Based Weighted KNN for Detecting Irony in Twitter

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Hernandez-Farias, DI.; Montes Gomez, M.; Escalante, H.; Rosso, P.; Patti, V. (2018). A Knowledge-Based Weighted KNN for Detecting Irony in Twitter. Lecture Notes in Computer Science. 11289:1-13. https://doi.org/10.1007/978-3-030-04497-8_16

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Título: A Knowledge-Based Weighted KNN for Detecting Irony in Twitter
Autor: Hernandez-Farias, Delia Irazu Montes Gomez, Manuel Escalante, Hugo Rosso, Paolo Patti, Viviana
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] In this work, we propose a variant of a well-known instancebased algorithm: WKNN. Our idea is to exploit task-dependent features in order to calculate the weight of the instances according to a novel paradigm: the ...[+]
Palabras clave: Instance-based algorithm , WKNN , Irony detection
Derechos de uso: Reserva de todos los derechos
Fuente:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-04497-8_16
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/978-3-030-04497-8_16
Título del congreso: 17th Mexican International Conference on Artificial Intelligence (MICAI 2018)
Lugar del congreso: Guadalajara, Mexico
Fecha congreso: Octubre 22-27,2018
Código del Proyecto:
info:eu-repo/grantAgreement/CONACyT//FC 2016-2410/
info:eu-repo/grantAgreement/MINECO//TIN2015-71147-C2-1-P/ES/COMPRENSION DEL LENGUAJE EN LOS MEDIOS DE COMUNICACION SOCIAL - REPRESENTANDO CONTEXTOS DE FORMA CONTINUA/
info:eu-repo/grantAgreement/UNITO//S1618_L2_BOSC_01/
Agradecimientos:
This research was funded by CONACYT project FC 2016-2410. The work of P. Rosso has been funded by the SomEMBED TIN2015-71147-C2-1-P MINECO research project. The work of V. Patti was partially funded by Progetto di Ateneo/CSP ...[+]
Tipo: Artículo Comunicación en congreso

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