Techniques for Multilingual Security-Related Event Extraction from Online News

  • Martin Atkinson
  • Mian Du
  • Jakub Piskorski
  • Hristo Tanev
  • Roman Yangarber
  • Vanni Zavarella
Part of the Studies in Computational Intelligence book series (SCI, volume 458)


This chapter presents a number of techniques for multilingual event extraction, the main task is to accurately and efficiently detect key information about security-related events from electronic news media and summarize it in the form of database-like structures. Gathering such information over time is an important task for developing global news surveillance systems, particularly in the context of security threats and mass emergencies. In particular, this chapter describes novel techniques for dealing with specific extraction tasks, including: an event type classification method based on domain-specific inference rules, an approach to event geo-tagging based on utilisation of lexico-semantic patterns, a simple method for cross-lingual event information fusion, and techniques for scoring the relevance rank of automatically extracted facts.


Inference Rule Locative Relation News Article Event Extraction Coast Guard 
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 2013

Authors and Affiliations

  • Martin Atkinson
    • 1
  • Mian Du
    • 3
  • Jakub Piskorski
    • 2
  • Hristo Tanev
    • 1
  • Roman Yangarber
    • 3
  • Vanni Zavarella
    • 1
  1. 1.JRCIspraItaly
  2. 2.FrontexWarsawPoland
  3. 3.Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland

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