Artificial Intelligence for e-Government: A View on Children’ Welfare

Abstract

This thesis aims to perform a holistic investigation concerning the use of artificial intelligence advance techniques in predicting children in danger of abuse or neglect. A dataset containing over 55322 cases from the Portuguese National Commission for the Promotion of the Rights and Protection of Children and Youth (CNPCJ) was collected and trained to uncover the patterns and additional findings. This research uses machine learning classification models to unveil the model with highest accuracy and robustness in the use predictive analytics in the children’s’ welfare field. This approach will allow social security services to understand the impact of underlying factors for further improvement of their services. Finally, this study develops a random forest predictive model to forecast children in risk, with an accuracy of 84.5%.