The Classification System for Serial Criminal Patterns (CSSCP) is an artificial intelligence computer system that assists law enforcement officials in identifying links between serial crimes. Working in conjunction with a neural network called a Kohonen network, CSSCP finds patterns in law enforcement databases by analyzing the characteristics of an offender, the criminal activities that have occurred, and the objects used in a crime. Once the links between crimes have been identified by CSSCP, law enforcement officials can then use the data that is produced to build leads or solve criminal cases. Through its capability to run autonomously, the CSSCP has proven that it can operate non-stop without any human interaction and can achieve results with much more accuracy and efficiency than a human. Background The Classification System for Serial Criminal Patterns was started by Professor Thomas Muscarello and Professor Kamal Dahbur at DePaul University in Chicago, Illinois in 1996 with the help of a Chicago Police Detective. Muscarello and Dahbur recognized the need for their hybrid system as a result of recognized deficiencies in police practices. These deficiencies were said to be a result of the police's difficulties in analyzing data and transforming it into information that could be useful in the investigation of crimes. In addition to assisting law enforcement officials interpret data, the CSSCP was also designed to help investigators determine which criminal data was critical to an investigation and which format it should be stored in. Although a similar project was previously undertaken by Timothy O'Shea, Muscarello and Dahbur noticed that problems existed with this proposed system because it relied on limited pre-processing and complex algorithms that lead to computational problems. The objective of Professor Muscarello and Professor Dahbur was to create an "automated methodology that can systematically identify groups of records as potential patterns for serial criminals, with a good degree of accuracy". System Design The CSSCP program was designed to work in three separate phases in conjunction with a Kohonen network. The three phases of CSSCP include: Pre-processing phase Neural network phase Heuristics system phase Pre-Processing Phase The Pre-Processing Phase of CSSCP is considered to be the most important phase of the system because it is the phase in which data is structured and put in a format that can be used by the neural network. This phase is where CSSCP will analyze the records it's provided, detect patterns among the data, and assign the