Percorrer por autor "Neves, Diogo Mota"
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- Using Machine Learning to classify responsible from non-responsible online gamblersPublication . Neves, Diogo Mota; Pereira, Isabel Cecília Correia da Silva Praça GomesIn recent years, responsible gaming (RG) has become increasingly important to companies whose main activity relies on betting or casino activities and, as more and more people have begun to gamble online. With the proliferation of online gambling, it has become easier for individuals to access gambling sites and place bets from the comfort of their own homes, which can increase the risk of non-responsible gaming practices. Betting companies, such as Betano, that prioritize responsible gaming are more likely to attract and retain customers, as individuals are more likely to trust and feel comfortable using a platform that takes steps to ensure that their gambling habits are safe and controlled. In addition to the business benefits, responsible gaming is also important from a social and ethical perspective. Gambling addiction can have serious consequences for individuals and their families, including financial, relationship, and mental health problems. By taking steps to promote responsible gaming, Betano can help to minimize the negative impacts of gambling and contribute to the well-being of its customers. This research paper will address the issue of responsible gaming for Betano by exploring the use of artificial intelligence (AI) and machine learning (ML) techniques to detect problematic gambling behaviors. By utilizing AI and ML, Betano can better understand and predict gambling behaviors and take proactive steps to promote responsible gaming. This project will analyze the potential benefits and limitations of using these technologies in the context of responsible gaming.