Abstract
In recent years problem of identifying terrorist threat has become a priority topic for government and military organizations. We base our ideas on new concepts of indirect association analysis to extract useful information for terrorist threat indication. Method introduces original approach to knowledge representation as a set of ontologies and semantic network, which are then processed by the inference algorithms and structure graph analysis. Described models consist of experience gathered from intelligence experts and several open Internet knowledge systems such as Global Terrorism Database, Profiles in Terror knowledge base. We managed to extract core information from several ontologies and fuse them into one domain model aimed to provide basis for indirect associations identification method.
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Chmielewski, M., Gałka, A., Jarema, P., Krasowski, K., Kosiński, A. (2009). Semantic Knowledge Representation in Terrorist Threat Analysis for Crisis Management Systems. In: Nguyen, N.T., Kowalczyk, R., Chen, SM. (eds) Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. ICCCI 2009. Lecture Notes in Computer Science(), vol 5796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04441-0_40
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DOI: https://doi.org/10.1007/978-3-642-04441-0_40
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