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A Survey of the Factors of Optimal Noise Reduction Algorithm for Terrorist Web Mining

R.D. Gaharwar, D.B. Shah, G.K.S. Gaharwar. Published in Algorithms.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: R.D. Gaharwar, D.B. Shah, G.K.S. Gaharwar
10.5120/cae2016652121

R D Gaharwar, D B Shah and G K S Gaharwar. Article: A Survey of the Factors of Optimal Noise Reduction Algorithm for Terrorist Web Mining. Communications on Applied Electronics 4(6):27-30, March 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {R.D. Gaharwar and D.B. Shah and G.K.S. Gaharwar},
	title = {Article: A Survey of the Factors of Optimal Noise Reduction Algorithm for Terrorist Web Mining},
	journal = {Communications on Applied Electronics},
	year = {2016},
	volume = {4},
	number = {6},
	pages = {27-30},
	month = {March},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Over the past few decades there have been frequent terrorist attacks around the world including India. This article describes Terrorist Network Mining and problems faced during studying such networks. A major challenge faced by the law enforcement agencies is the large crime ‘raw’ data volumes and the lack of sophisticated network analysis tools and techniques to utilize the data effectively and efficiently. This article states different data collection techniques used for terrorist networks. The major challenge is the development of the optimal noise reduction algorithm which will help in creating accurate linkage map of terrorist network without the loss of any key player node. This article successfully lists the factors that can be taken under consideration during generation of optimal noise reduction algorithm for Terrorist Web Mining. Once the accurate linkage map is generated the identification and removal of the key player for the destabilization of terrorist networks will become lot easier.

References

  1. T. Bhatia, "Link Analysis Algorithm For Web Mining”, International Journal of Computer Science And Technology, Vol. 2, Issue 2, June 2011, pp. 243-246.
  2. Monika Yadav and Pradeep Mittal, "Web Mining: An Introduction," International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, no. 3, March 2013, pp. 683-687.
  3. N. Chaurasia, A. Tiwari, ”Novel Algorithm for Terrorist Network Mining”, International Journal of Computer Science And Communication Technologies, Vol. 6, no. 1, July 2013, pp. 898-903.
  4. R. D. Gaharwar, D. B. Shah, G.K.S. Gaharwar, "Proposed Architecture for Terrorist Web Miner," International Journal of Computer Applications, Vol. 128, no. 9, October 2015, pp. 18-20.
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  7. R. . D. Gaharwar, D. B. Shah, and G.K.S. Gaharwar, "Terrorist Network Mining: Issues and Challenges," International Journal of Advance Research in Science and Engineering, Vol. 4, no. 1, 2015, pp. 33-37.
  8. V. E. Krebs, "Mapping networks of terrorist cells”, Connections 24, March 2001, pp. 43–52.
  9. Y. Elovici, A. Kandel, M. Last, B. Shapira, O. Zaafrany, “Using Data Mining Techniques for Detecting Terror-Related Activities on the Web”, Proc. Second Int’l Conf. on Computer and Electrical Engineering (ICCEE 2009), 2009, pp. 152-157
  10. V. E. Krebs, (2002), “Uncloacking Terrorist Networks”, First Monday, Vol. 7, 2002, pp. 4 - 1.

Keywords

Social Network Analysis, Terrorist Networks, Terrorist Network Mining