Application of the behavioral investigative support system for profiling perpetrators of serial sexual assaults

Abstract

The authors developed a data-based profiling system in order to support offender profiling. The system stored incident records of prior offenders. Inputting offence details of an unsolved incident, a probability score was assigned to each prior offender in the system; the score represented the behavioral similarity with the unsolved incident. The system then ranked all offenders in the system according to the probability scores, and prioritized the high-ranked offenders as possible suspects. Moreover, the system inferred the characteristics of unknown offenders by accumulating characteristics of the high-ranked offenders. The system achieved promising accuracy, especially for linking crimes to perpetrators. In 45 out of 81 simulation trials, the target offenders were retrieved as a rank score of 1 from among 868 sex offenders.