Knowledge Engineering for Crime Investigation
Wilmuth Müller, Dirk Mühlenberg, Dirk Pallmer, Uwe Zeltmann, Christian Ellmauer, Francisco José Pérez Carrasco, Alberto Garcia Garcia, Konstantinos Demestichas, Nikolaos Peppes, Despoina Touska, Konstantinos Gkountakos, Eva Muñoz Navarro, Santiago Martinez
Proceedings of the 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022, Vol. III, pp. 64-69 (2022); https://doi.org/10.54808/WMSCI2022.03.64
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The 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022
Virtual Conference July 12 - 15, 2022 Proceedings of WMSCI 2022 ISSN: 2771-0947 (Print) ISBN (Volume III): 978-1-950492-66-4 (Print) |
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Abstract
Building upon the possibilities of technologies like ontology engineering, knowledge representational models, text mining, and semantic reasoning, our work presented in this paper, which has been performed within the collaborative research project PREVISION (Prediction and Visual Intelligence for Security Information), co-funded by the European Commission within Horizon 2020 programme, is going to support Law Enforcement Agencies (LEAs) in their critical need to exploit all available resources, and handling the large amount of diversified media modalities to effectively carry out criminal investigation.
A series of tools have been developed within PREVISION which provide LEAS with the capabilities of analyzing and exploiting multiple massive data streams coming from social networks, the open web, the Darknet, traffic and financial data sources, etc. and to semantically integrate these into dynamic knowledge graphs that capture the structure, interrelations and trends of terrorist groups and individuals and OGCs. The paper at hand focuses on the developed ontology and the tools for text mining, Extract Transform Load, Semantic Reasoning and the knowledge base and knowledge visualization. |
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