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 |
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Format: | Artikel |
Sprache: | eng |
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