The "Artificial Neural Network Systems for Classification of Offenders in Murder and Rape Cases" project developed two software prototypes that demonstrate developed algorithms for analyzing and comparing large databases of crime data. The CATCH (Computer Aided Tracking and Characterization of Homicides) and CATCHRAPE software applications analyze homicide data and sexual assault data, respectively. Development of CATCH was made possible with the HITS (Homicide Investigation Tracking System) database system. The HITS system provided the required historical crime data for CATCH to learn offender behavior so that new unsolved crimes can be characterized for analysis and comparison. CATCH characterizes an unknown offender by comparing his or her crime to known offenders of other crimes where the offenders' behavior was similar. The information includes level of education, type of work, physical appearance, misuse of alcohol and drugs, etc. The underlying assumption is that individuals who otherwise behave similarly, may also commit crimes with similar behavior. Bibliography
Downloads
Similar Publications
- The measurement and prevalence of violent crime in the United States: persons, places, and times
- Evaluation and validation of ion mobility spectrometry for presumptive testing targeting the organic constituents of firearms discharge residue
- The Impact of Relationship Dynamics on the Detection and Reporting of Elder Abuse Occurring in Domestic Settings