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 *3) Display the hierarchy of com­plex criminal network problems from the general to specific level;
 * 4) Develop and use decision rules which accelerate computation time, as well as allow the investigator to understand the problem better;
 * 5) Receive advice and consulta­tion from the expert system on new and existing cases based upon prior knowledge captured by the system;
 * 6) Preserve information in an ac­tive form as a knowledge base, rather than a mere passive listing of facts and figures;
 * 7) Train novices to think as an experienced crime profiler would; and
 * 8) Create and preserve in an active environment a system that is not subject to human failings, will respond to cons­tant streams of data, and can generalize large bodies of knowledge.

AI applications show great poten­tial for solving complicated crime pro­filing and assessment problems. Research is currently being conducted in two such uses which will be inte­grated into the NCAVC's AI computer project.

Social network analysis is a behavioral science-oriented approach that describes the interaction patterns between people. $4$ This analysis can be used to identify possible courses of action an individual or group might take, as well as to surmise as to the hierarchical structure of an organization or group. Examples of the application of social network analyses include struc­tures of organized crime syndicates, motorcycle gangs, and terrorist groups. NCAVC staff members are developing AI procedures to manipulate data and compute the probable hierarchies and interactions of complex organizations. The behavioral analysis of threaten­ing oral and written communications in extortions, bombings, and terrorist incidents is another viable application of artificial intelligence technology to real-world law enforcement problems.$5$

The NCAVC is actively researching and experimenting with computer-assisted linguistic analysis techniques to evaluate the content of these com­munications in an effort to determine the authorship profile and assess the viability of the threat.

Summary

Presented in this article have been the systems approach to the manage­ment of violent crime data and the development of an artificial intelligence crime profiling computer system for the National Center for the Analysis of Violent Crime. The major benefit of this effort is an effective management infor­mation system which will track the activities of the program, assess the impact of law enforcement efforts against violent crime, and introduce automated computer-assisted profiling technology. FBI

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 * $1$ D. J . Icove. et al.,Incendiary Fire Analysis and Invastigation, Open Fire Service Learning Program (Lexington. MA: Ginn Publishing Co. 1984); D. J. Icove, V. B. Wherry, and J. D. Schroeder, Combating Arson-For Profit: Advanced Techniques for Investigators (Columbus, OH: Battelle Press, 1980).
 * $2$ J. L. Bryan and D. J. tcove, "Recent Advances In Computer Assisted Arson Investigation," Fire Journal. National Fire Protection Association. vol. 71, No. 1, January 1977; D. J. Icove and H. L. Crisman, "Application of Pattern Recognition to Arson Investigation," Fire Technology. National Fire Protection Association, February 1975; "Arson: the Prevention Chain," National Clearinghouse for Criminal Justice Systems, U.S. Department of Justice, May 1980.
 * $3$ B. G. Buchanan and E. H. Shortliffe, Rule·Based Expert Systems (Reading, MA: Addison·Wesley Publishing Co., Inc., 1984).
 * $4$ R. H. Davis, "Social Network Analysis: An Aid in Conspiracy Investigations," FBI Law Enforcement Bulletin, vol. 50, No. 12, December 1981.
 * $5$ M. S. Miron and J. E. Douglas, "Threat Analysis: The Psychollnguistic Approach," FBI Law Enforcement Bulletin. vol. 48. No. 9., September 1979; U. Perret, "Computer Assisted Forensic Linguistic System 'TEXTOR,'" IEEE International Conference: Security through Science and Technology, September 1980.

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