The author(s) shown below used Federal funds provided by the U.S.
Department of Justice and prepared the following final report:
Artificial Neural Network System for
Classification of Offenders in Murder and Rape
Cases, Executive Summary
This report has not been published by the U.S. Department of Justice.
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the official position or policies of the U.S.
Department of Justice.
Artificial Neural Network System for Classification of Offenders in
Murder and Rape Cases
Prepared by Lars Kangas for the
National Institute of Justice,
Office of Science and Technology
Under Award Number 97-IJ-CX-KO07
When a serial offender strikes, it usually means that the investigation is unprecedented for that
police agency. The volume of incoming leads and pieces of information in the case(s) can be
overwhelming as evidenced by the thousands of leads gathered in the Ted Bundy Murders,
Atlanta Child Murders, and the Green River Murders. Serial cases can be long-term
investigations in which the suspect remains unknown and continues to perpetrate crimes. With
state and local murder investigative systems beginning to crop up, it will become impohant to
manage that information in a timely and efficient way by developing computer programs to assist
in that task. One vital function will be to compare violent crime cases from different jurisdictions
so investigators can approach the investigation knowing that similar cases exist.
The “Artificial Neural Network System for Classification of Offenders in Murder and Rape
Cases” project developed two software prototypes that demonstrate dev