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A Semantic Knowledge Discovery Framework for Detecting Online Terrorist Networks

  • Andrea Ciapetti
  • Giulia Ruggiero
  • Daniele TotiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11296)

Abstract

This paper presents a knowledge discovery framework, with the purpose of detecting terrorist presence in terms of potential suspects and networks on the open and Deep Web. The framework combines information extraction methods and tools and natural language processing techniques, together with semantic information derived from social network analysis, in order to automatically process online content coming from disparate sources and identify people and relationships that may be linked to terrorist activities. This framework has been developed within the context of the DANTE Horizon 2020 project, as part of a larger international effort to detect and analyze terrorist-related content from online sources and help international police organizations in their investigations against crime and terrorism.

Keywords

Natural language processing Knowledge discovery Group discovery Ontology building Named entity recognition 

Notes

Acknowledgments

The work presented in this paper was supported by the European Commission under contract H2020-700367 DANTE.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Innovation Engineering S.r.l.RomeItaly
  2. 2.Department of SciencesRoma Tre UniversityRomeItaly

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