Abstract
The objective of this paper is to analyze different classification algorithms in data mining to predict terrorist group involved in an incident. Terrorist groups are highly dynamic and mysterious, which makes it challenging to track their activities and prevent incidents. Prediction of terrorist group using chronological data of terrorist activities has been less explored due to the lack of detailed terrorist data which contain terrorist group’s attacks and activities. The study tries to investigate the GTD through classification method for pattern discovery. This research paper proposes a framework for terrorist group prediction that is based on data mining classification techniques. The framework has been validated with the experimental results using WEKA tool.
Keywords: – GTD, Counter Terrorism, Terrorist Group Prediction, Classification, WEKA.
P. L. Verma1, Sanjay Dwivedi2*, Shivendra Kumar Dwivedi3
1Department of Physics, Govt. Vivekanand P.G. College, Maihar-485771, M.P., India
2Govt. SGS P.G. College, Sishi-486661, M.P., India
3Sharda Mahavidyalaya, Sarlanagar-485114, M. P., India