VCCM Mining: Mining Virtual Community Core Members Based on Gene Expression Programming
Intelligence operation against the terrorist network has been studied extensively with the aim to mine the clues and traces of terrorists. The contributions of this paper include: (1) introducing a new approach to classify terrorists based on Gene Expression Programming (GEP); (2) analyzing the characteristics of the terrorist organization, and proposing an algorithm called Create Virtual Community (CVC) based on tree-structure to create a virtual community; (3) proposing a formal definition of Virtual Community (VC) and the VCCM Mining algorithm to mine the core members of a virtual community. Experimental results demonstrate the effectiveness of VCCM Mining.
Unable to display preview. Download preview PDF.
- 1.Wentz, L.K., Lee, W.: Wagenhals:Effects Based Operations for Transnational Terrorist Organizations: Assessing Alternative Courses of Action to Mitigate Terrorist Threats. In: Proceedings of Command and Control Research and Technology Symposium, San Diego (2004)Google Scholar
- 3.Ferreira, C.: Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, Angra do Heroismo, Portugal (2002)Google Scholar
- 4.Matt Crenson: Math wizards offer help in fighting terrorism (2004), http://www.azstarnet.com/dailystar/relatedarticles/42692.php
- 5.Qiao, S., Tang, C., Yu, Z., Wei, J., Li, H., Wu, L.: Mining Virtual Community Structure Based on SVM. Computer Science 32(7), 208–212 (2005)Google Scholar
- 7.Ferreira, C.: Gene Expression Programming in Problem Solving. Soft Computing and Industry: Recent Applications, pp. 635–654. Springer, Heidelberg (2002)Google Scholar
- 8.Platt, J.: Sequential minimal optimization: A fast algorithm for training support vector machines. Advances in Kernel Methods-Support Vector learning, pp. 185–208. MIT Press, Cambridge (1999)Google Scholar