| 1 |
A Machine learning approach to human trafficking prediction |
This study introduces a comprehensive method for identifying and predicting human trafficking using Machine-Learning. Given the urgent need for more efficient prevention and intervention techniques in addressing this pervasive crime, the conventional manual approaches are time-consuming. The proposed method automates the identification and prediction processes by leveraging various Machine- Learning techniques. It analyzes extensive data, including social media posts, individual demographics, and internet activity, to pinpoint potential victims and forecast their likelihood of involvement in human trafficking. Utilizing methods such as decision trees, support vector machines, and neural networks enhances the system’s effectiveness. Employing cross-validation, model evaluation, and feature selection further boosts the accuracy of the system. This technique offers a substantial improvement in accuracy, aiding law enforcement organizations in their endeavors to combat this heinous crime. |
Quick Links
