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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Detalles Bibliográficos
Autores principales: Ding, Fangyu, Ge, Quansheng, Jiang, Dong, Fu, Jingying, Hao, Mengmeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5462416/
https://www.ncbi.nlm.nih.gov/pubmed/28591138
http://dx.doi.org/10.1371/journal.pone.0179057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5462416/
https://www.ncbi.nlm.nih.gov/pubmed/28591138
http://dx.doi.org/10.1371/journal.pone.0179057

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