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Research Article | Open Access |

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

Author 1: Semeh BEN SALEM Author 2: Sami NAOUALI
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 8 · Published 2016

DOI: 10.14569/IJACSA.2016.070838

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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).

Keywords

clustering pattern recognition multidimensional databases distance measurement Khi2 formula Euclidean distance Multiple Correspondence Analysis

How to Cite this Article

SALEM, S. B., & NAOUALI, S. (2016). Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database. International Journal of Advanced Computer Science and Applications, 7(8). https://doi.org/10.14569/IJACSA.2016.070838

SALEM, Semeh BEN, and Sami NAOUALI. "Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database." International Journal of Advanced Computer Science and Applications, vol. 7, no. 8, 2016, https://doi.org/10.14569/IJACSA.2016.070838.

@article{SALEM2016,
  title     = {Pattern Recognition Approach in Multidimensional Databases: Application to the Global Terrorism Database},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {8},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Semeh BEN SALEM and Sami NAOUALI},
  doi       = {10.14569/IJACSA.2016.070838},
  url       = {https://doi.org/10.14569/IJACSA.2016.070838}
}

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Volume 17 No. 11, November 2026
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