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NCJ Number: NCJ 190983     Find in a Library
Title: Artificial Neural Network System for Classification of Offenders in Murder and Rape Cases, Executive Summary
  Document URL: PDF 
Author(s): Lars Kangas
Corporate Author: Battelle Memorial Institute
United States of America
Date Published: 10/2000
Page Count: 5
  Series: NIJ Research Report
  Annotation: This is an Executive Summary of a report on an artificial neural network system for classifying offenders in murder and rape cases.
Abstract: 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
Main Term(s): Criminology
Index Term(s): Offenders ; Rape ; Computer software ; Science and Technology ; Murder ; Offender classification ; Offender profiles ; Databases ; NIJ final report
Sponsoring Agency: National Institute of Justice (NIJ)
US Department of Justice
Office of Justice Programs
United States of America
Grant Number: 97-IJ-CX-K007
Sale Source: NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States of America

Battelle Memorial Institute
Pacific Northwest Division
Richland, WA 99352
United States of America
Type: Report (Study/Research)
Country: United States of America
Language: English
Note: For the complete report, see NCJ-190984.
  To cite this abstract, use the following link:

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