Title :
Design and development of an early warning system to prevent terrorist attacks
Author :
Memon, Nasrullah ; Wiil, Uffe Kock ; Qureshi, A.R.
Author_Institution :
Maersk Mc-Kinney Moller Inst., Univ. of Southern Denmark, Odense, Denmark
Abstract :
EWAS is an early warning prototype that collects and analyzes news items from the European media monitor. Although, it currently processes news articles, it can easily be adapted to any other form of text. Data mining functions performed by the system are categorization, clustering, and named entity extraction. The main design concern of the system is scalability, which is achieved by a modular architecture that allows multiple instances of the same component to run in parallel. The main objective behind this research is to develop a system to identify ldquowho is doing whatrdquo to estimate ldquowho can do whatrdquo in order to predict ldquowhat can really happen tomorrowrdquo.
Keywords :
data mining; emergency services; pattern clustering; terrorism; text analysis; EWAS; European media monitor; data mining; early warning system; modular architecture; named entity extraction; news item analysis; terrorist attack prevention; text categorization; text clustering; Alarm systems; Data mining; Event detection; Government; Monitoring; Portals; Prototypes; Risk management; Scalability; Terrorism; European media monitor; SOMA Terrorist Organization Portal; Spiner; early warning system; iMiner;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234424