ASKARI: A Crime Text Mining Approach

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Author(s): Caroline Chibelushi (Straffordshire University, UK), Bernadette Sharp (Straffordshire University, UK)and Hanifa Shah (Straffordshire University, UK)
Copyright: 2006
Pages: 20
Source title: Digital Crime and Forensic Science in Cyberspace
Source Author(s)/Editor(s): Panagiotis Kanellis (Information Society S.A., Greece), Evangelos Kiountouzis (Athens University, Greece), Nicholas Kolokotronis (Universitiy of Peloponnese, Greece)and Drakoulis Martakos (National and Kapodistrian University of Athens, Greece)
DOI: 10.4018/978-1-59140-872-7.ch008

Keywords: Digital Crime & Forensics / Information Science Reference / IT Security and Ethics / Security & Forensics

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Abstract

The advancement of multimedia and communication systems has not only provided faster and better communication facilities but also facilitated easier means to organized crime. Concern about national security has increased significantly in the recent years due to the increase in organized crimes, leading to increasing amounts of data available for investigation by criminal analysts. The opportunity to analyze this data to determine patterns of criminal behavior, monitor, and predict criminal activities coexists with the threat of information overload. A large amount of information, which is stored in textual and unstructured form, contains a valuable untapped source of data. Data mining and text mining are two key technologies suited to the discovery of underlying patterns in large data sets. This chapter reviews the use of text mining techniques in crime detection projects and describes in detail the text mining approach used in the proposed ASKARI project.

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