Visualization of Crime Data Using Self-organizing Map (SOM) and Improvement in SOM: A Review and Available Tools

Abstract

Recently, the major challenge faced by all intelligencegathering and law-enforcement organizations is to efficiently and accurately analyze the huge volumes of crime data. Self-organizing map (SOM) can be used to visualize crime data into more comprehensible presentation. Although visualization by using SOM has been done by many researchers, a literature review on the subject focuses on crime data has yet to be implemented. Thus, this study reviews researches on visualization of crime data using SOM and improvement in SOM (Fuzzy SOM or FSOM) together with their available software tools. Information and related works on visualization using SOM and FSOM were studied to fully understand the situation. The result of this study clearly shows that SOM and FSOM have been applied to visualize data in various fields of study. However, there is only limited use of them for visualization of crime data by the researchers. The popular software tool for visualization of crime data using SOM is Matlab, followed by Viscovery SOMine, R, GeoVISTA Studio and C/C++ compiler. Finally, this study concludes with a few suggestions for future researches on visualization of crime data.

Indexed Crime Data Visualization Utilizing Self-Organizing Map Algorithm

“…Visualization of crime data is very important in order to identify the crime pattern and support decision making in crime prevention [7]. Moreover, this technique is important as it can represent crime data into more understandable presentation and can be used to support decision making processes.…”