Autor según el artículo: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M. Dolores;
Departamento: Enginyeria Informàtica i Matemàtiques Filologies Romàniques
Autor/es de la URV: Jiménez López, María Dolores / Moreno Ribas, Antonio
Palabras clave: Machine learning Gender detection Author profiling
Resumen: Automatic gender detection has attracted the attention of many research fields such as forensic linguistics or marketing. Within these areas, gender detection has been approached as a classification problem and, for this reason, supervised Machine Learning algorithms such as Naive Bayes, Logistic Regression and Support Vector Machines, among others, have been employed. The latter algorithm has exhibited a better performance on gender detection. In recent years, with the development of Deep Learning methods, various neural networks structures such as Convolutional Neural Networks have been designed for gender detection. However, Deep Learning methods have led to a loss in the interpretability of the models. In this article, we review the AI techniques applied on gender detection.
Áreas temáticas: Interdisciplinar Engenharias iv Engenharias iii Computer science, interdisciplinary applications Computer science, artificial intelligence Ciências ambientais Ciência da computação Artificial intelligence
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: mariadolores.jimenez@urv.cat antonio.moreno@urv.cat
Identificador del autor: 0000-0001-5544-3210 0000-0003-3945-2314
Fecha de alta del registro: 2024-01-13
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://www.worldscientific.com/doi/10.1142/S0218213022410020
URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: International Journal On Artificial Intelligence Tools. 31 (03):
Referencia de l'ítem segons les normes APA: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M. Dolores; (2022). Machine Learning Methods for Automatic Gender Detection. International Journal On Artificial Intelligence Tools, 31(03), -. DOI: 10.1142/S0218213022410020
DOI del artículo: 10.1142/S0218213022410020
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2022
Tipo de publicación: Journal Publications
Repositori URV