GADGET - Online Gambling Addiction Detection

• Autor(a) principal: Castelli, Mauro
• Data de Publicação: 2021
• Outros Autores: Fallacara, Enrico, Manzoni, Luca
• Tipo de documento: Livro
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/110872
• topic: Machine Learning; Time Series; Clustering; Gambling; Addiction

This chapter describes an automatic tool that highlights potential pathological online gamblers using machine learning time series clustering algorithms. The project relies on data related to Portuguese gamblers.A theoretical overview of the two different clustering algorithms considered in this project is presented. We also provide some implementation details and the changes that we have introduced to make the algorithm executable in a parallel and efficient manner. Finally, the results obtained by the two different techniques are presented, highlighting especially the clusters of pathological gamblers obtained. This work represents a starting point for a possible future system where the individuals at risk are notified of their dangerous condition, preventing possible future gambling disorders or risky behavior.