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Machine Learning Methods for Automatic Gender Detection

  • Dades identificatives

    Identificador: imarina:9262211
    Handle: https://hdl.handle.net/20.500.11797/imarina9262211
    Autors:
    Morales Sanchez, DamianMoreno, AntonioJimenez Lopez, M. Dolores
    Resum:
    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.

  • Altres:

    Autor segons l'article: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M. Dolores;
    Departament: Enginyeria Informàtica i Matemàtiques Filologies Romàniques
    Autor/s de la URV: Jiménez López, María Dolores / Moreno Ribas, Antonio
    Paraules clau: Machine learning Gender detection Author profiling
    Resum: 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.
    Àrees temàtiques: Interdisciplinar Engenharias iv Engenharias iii Computer science, interdisciplinary applications Computer science, artificial intelligence Ciências ambientais Ciência da computação Artificial intelligence
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: antonio.moreno@urv.cat mariadolores.jimenez@urv.cat
    Identificador de l'autor: 0000-0003-3945-2314 0000-0001-5544-3210
    Data d'alta del registre: 2024-09-07
    Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: International Journal On Artificial Intelligence Tools. 31 (03):
    Referència 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
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2022
    Tipus de publicació: Journal Publications

  • Paraules clau:

    Artificial Intelligence,Computer Science, Artificial Intelligence,Computer Science, Interdisciplinary Applications
    Machine learning
    Gender detection
    Author profiling
    Interdisciplinar
    Engenharias iv
    Engenharias iii
    Computer science, interdisciplinary applications
    Computer science, artificial intelligence
    Ciências ambientais
    Ciência da computação
    Artificial intelligence

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