Detecting Terrorism Incidence Type from News Summary

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 126)


The paper presents the experiments to detect terrorism incidence type from news summary data. We have applied classification techniques on news summary data to analyze the incidence and detect the type of incidence. A number of experiments are conducted using various classification algorithms and results show that a simple decision tree classifier can learn incidence type with satisfactory results from news data.


GTD Classification Decision tree Naïve Bayes SVM 


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Maersk McKinney Moller InstituteUniversity of SouthernOdenseDenmark
  2. 2.University of SindhJamshoroPakistan

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