Terrorist Activity Evaluation and Pattern Detection (TAE&PD) in Afghanistan: A Knowledge Discovery and Data Mining (KDDM) Approach for Counter-Terrorism
POLYTECHNIC UNIV OF PUERTO RICO SAN JUAN
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Data mining DM is primarily used by businesses to discover customer tendencies to guarantee future profit opportunities. In the TAEPD project we intend to incorporate a KDDM methodology using open source applications to gather, preprocess, model, evaluate and identify patterns of terrorism activity that may prove useful to counter-terrorism and strengthen homeland security in Afghanistan. We will experiment using real terrorism incidents data from the Worldwide Incidents Tracking System WITS of the National Counterterrorism Center NCTC. The project seeks to discover terrorism trends based on specific incident factors, help in the evaluation of war in Afghanistan and demonstrate a KDDM approach that could be applied proof of concept to national security. Project results may uncover valuable information regarding terrorist hot spots to determine geographical mobilization of security forces resources in the region.
- Information Science
- Unconventional Warfare