Articles producció científicaFilologies Romàniques

Machine Learning Methods for Automatic Gender Detection

  • Identification data

    Identifier:  imarina:9262211
    Authors:  Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M Dolores
    Abstract:
    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.
  • Others:

    Link to the original source: https://www.worldscientific.com/doi/10.1142/S0218213022410020
    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), 2241002-. DOI: 10.1142/S0218213022410020
    Paper original source: International Journal On Artificial Intelligence Tools. 31 (03): 2241002-
    Article's DOI: 10.1142/S0218213022410020
    Journal publication year: 2022
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/acceptedVersion
    Record's date: 2025-01-28
    URV's Author/s: Jiménez López, María Dolores / Moreno Ribas, Antonio
    Department: Enginyeria Informàtica i Matemàtiques, Filologies Romàniques
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Morales Sanchez, Damian; Moreno, Antonio; Jimenez Lopez, M Dolores
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Thematic Areas: Interdisciplinar, Engenharias iv, Engenharias iii, Computer science, interdisciplinary applications, Computer science, artificial intelligence, Ciências ambientais, Ciência da computação, Artificial intelligence
    Author's mail: antonio.moreno@urv.cat, mariadolores.jimenez@urv.cat
  • Keywords:

    Machine learning
    Gender detection
    Author profiling
    Artificial Intelligence
    Computer Science
    Interdisciplinary Applications
    Interdisciplinar
    Engenharias iv
    Engenharias iii
    Ciências ambientais
    Ciência da computação
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