Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database

Abstract

This paper presents a pattern recognition approach in multidimensional databases. The approach is based on a clustering method using the distance measurement between a reference profile and the database observations. Two distance measurements will be proposed: an adaptation of the Khi2 formula to the multidimensional context, extracted from the Multiple Correspondence Analysis (MCA), and the Euclidean distance. A comparison between the two distances will be provided to retain the most efficient one for the multidimensional clustering context. The proposed approach will be applied to a real case study representing armed attacks worldwide stored in the Global Terrorism Database (GTD).

Authors and Affiliations

Semeh SALEM, Sami NAOUALI

Keywords

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  • EP ID EP164779
  • DOI 10.14569/IJACSA.2016.070838
  • Views 117
  • Downloads 0

How To Cite

Semeh SALEM, Sami NAOUALI (2016). Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database. International Journal of Advanced Computer Science & Applications, 7(8), 280-286. https://europub.co.uk/articles/-A-164779