Automating Event Extraction for the Security Domain

  • Clive Best
  • Jakub Piskorski
  • Bruno Pouliquen
  • Ralf Steinberger
  • Hristo Tanev
Part of the Studies in Computational Intelligence book series (SCI, volume 135)


This chapter presents on-going efforts at the Joint-Research Center of the European Commission for automating event extraction from news articles collected through the Internet with the Europe Media Monitor system. Event extraction builds on techniques developed over several years in the fields of information extraction, whose basic goal is to derive quantitative data from unstructured text. The motivation for automated event tracking is to provide objective incident data with broad coverage on terrorist incidents and violent conflicts from around the world. This quantitative data then forms the basis for populating incident databases and systems for trend analysis and risk assessment.

A discussion of the technical requirements for information extraction and the approach adopted by the authors is presented. In particular, we deploy lightweight methods for entity extraction and a machine-learning technique for pattern-based event extraction. A preliminary evaluation of the results shows that the accuracy is already acceptable. Future directions of improving the approach are also discussed.


News Article Name Entity Recognition Violent Event Event Extraction Security Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Clive Best
    • 1
  • Jakub Piskorski
    • 1
  • Bruno Pouliquen
    • 1
  • Ralf Steinberger
    • 1
  • Hristo Tanev
    • 1
  1. 1.Joint Research Center of the European CommissionWeb and Language Technology Group of IPSCItaly

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