A STRATEGY FOR GENDER IDENTIFICATION IN OPEN DATA REPOSITORIES USING AN ARTIFICIAL NEURAL NETWORK MODEL
Sérgio José de Sousa, Monique de Oliveira Santiago, Thiago Magela Rodrigues Dias, ADILSON LUIZ PINTO · CONTECSI - International Conference on Information Systems and Technology Management · 2019
Many open datasets do not present information about gender, which makes it difficult to analyze this type of information, such as the identification of polarities and inequalities. Some works try to perform this classification using the first name and using traditional techniques like SVM, other than this, this work tries to find a relation between the characters of the full name in order to identify a possible gender for the names. This neural network model proved to be very effective reaching a 98.99% accuracy.