Decision support components and crime data mining for assistance in forensic investigation processes

The problem is addressed to developing of multi-component knowledge management system for crime investigation domain which will integrate many types of decision support methods: ontology-based system, dynamic modeling for scenario analysis, data mining for information retrieval and dissemination, ect. The methods of artificial intelligence helpful in the management of repository with impartial crime information and situation recognition are discussed. The unified approach is proposed using different data analysis strategies for integration knowledge with retrieval of relevant information from different database systems. The aiding advisory processes are helpful in relevant pattern recognition and crime investigation. The architecture of decision support repository includes a model of the problem solution strategies that allows choosing an appropriate multidimensional statistical method, a case-based reasoning mechanism. The paper outline the different components of decision support and illustrate the integration possibilities with data mining technologies of crime profile data warehouses.