Applying unsupervised machine learning to counterterrorism
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DOI: 10.1007/s42001-022-00164-w
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- Fangyu Ding & Quansheng Ge & Dong Jiang & Jingying Fu & Mengmeng Hao, 2017. "Understanding the dynamics of terrorism events with multiple-discipline datasets and machine learning approach," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-11, June.
- Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
- Yilmaz Bayar & Marius Dan Gavriletea, 2018. "Peace, terrorism and economic growth in Middle East and North African countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2373-2392, September.
- Ahmed Aleroud & Aryya Gangopadhyay, 2018. "Multimode co-clustering for analyzing terrorist networks," Information Systems Frontiers, Springer, vol. 20(5), pages 1053-1074, October.
- M. Irfan Uddin & Nazir Zada & Furqan Aziz & Yousaf Saeed & Asim Zeb & Syed Atif Ali Shah & Mahmoud Ahmad Al-Khasawneh & Marwan Mahmoud, 2020. "Prediction of Future Terrorist Activities Using Deep Neural Networks," Complexity, Hindawi, vol. 2020, pages 1-16, April.
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Keywords
Data wrangling; Local indicators of spatial association; Nonlinear projection; Statistical learning; Text mining;All these keywords.
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