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Detecting Terrorism Incidence Type from News Summary

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

Abstract

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.

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Correspondence to Sarwat Nizamani .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Nizamani, S., Memon, N. (2012). Detecting Terrorism Incidence Type from News Summary. In: Thaung, K. (eds) Advanced Information Technology in Education. Advances in Intelligent and Soft Computing, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25908-1_14

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  • DOI: https://doi.org/10.1007/978-3-642-25908-1_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25907-4

  • Online ISBN: 978-3-642-25908-1

  • eBook Packages: EngineeringEngineering (R0)

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