Classification System for Serial Criminal Patterns

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.

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.

[3] The CSSCP program was designed to work in three separate phases in conjunction with a Kohonen network.

The four functions include: The Neural Network phase of CSSCP is where machine learning algorithms are used for clustering and prediction tasks.

By the end of the neural network phase, all of the input data will have been analyzed, grouped, and classified into patterns that will become the basis for which the final results depend on.

The first use of CSSCP was during a trial study in which statistics from three years of armed robbery cases were analyzed.

[citation needed] The CSSCP program is designed to assist law enforcement officials who constantly deal with large volumes of criminal cases beyond what their departments can effectively handle by providing them with an inexpensive tool that can reduce investigation costs and department man-power.

[6] Through its ability to continuously operate accurately at a rate of ten times faster than a team of detectives doing the same type of work, CSSCP has begun to draw interest from law enforcement agencies all over the world that are looking for tools that can enhance security.