Understanding the dynamics of terrorism events with multiple-discipline datasets and machine learning approach

Terror events can cause profound consequences for the whole society. Finding out the regularity of terrorist attacks has important meaning for the global counter-terrorism strategy. In the present study, we demonstrate a novel method using relatively popular and robust machine learning methods to si...

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Veröffentlicht in:PloS one 2017-06, Vol.12 (6), p.e0179057-e0179057
Hauptverfasser: Ding, Fangyu, Ge, Quansheng, Jiang, Dong, Fu, Jingying, Hao, Mengmeng
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Sprache:eng
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