Data association methods with applications to law enforcement

Associating records in a large database that are related but not exact matches has importance in a variety of applications. In law enforcement, this task enables crime analysts to associate incidents possibly resulting from the same individual or group of individuals. In practice, most crime analysts perform this task manually by searching through incident reports looking for similarities. This paper describes automated approaches to data association. We report tests showing that our data association methods significantly reduce the time required by manual methods with accuracy comparable to experienced crime analysts. In comparison to analysis using the structured query language, or methods were both faster and more accurate.