Criminal Relation Exploration Tool for Law Enforcement Knowledge Management

Understanding relations between offenders in organized crimes is important for law enforcement and intelligence agencies to detect, prevent, and respond to crimes and terrorism events. However, several challenges (e.g., information overload, difficulty of relation search and extraction of relation patterns) face the task of criminal relation exploration. In this paper we present our ongoing research that develops an intelligent knowledge management system to help identify criminal relations from large amounts of crime incident records, search for the strongest relation paths between criminals, and extract and browse relation patterns and structural properties of a criminal network. We employ the concept space approach, shortestpath algorithms, and social network analysis techniques to achieve these goals. The preliminary results from evaluation studies show that our system can achieve a higher efficiency in criminal relation exploration than existing systems. Future work will be done to extend the system evaluation and analyze the dynamics of criminal networks.