| 期刊全稱 | A Machine Learning Based Model of Boko Haram | | 影響因子2023 | V. S. Subrahmanian,Chiara Pulice,Jacob Bonen-Clark | | 視頻video | http://file.papertrans.cn/142/141369/141369.mp4 | | 發(fā)行地址 | The first quantitative study of Boko Haram.The first book to provide a machine learning predictive model of attacks by Boko Haram.The first book that validates a counter-terrorism predictive model wit | | 學(xué)科分類 | Terrorism, Security, and Computation | | 圖書封面 |  | | 影響因子 | .This is the first study of Boko Haram that brings advanced data-driven, machine learning models to both learn models capable of predicting a wide range of attacks carried out by Boko Haram, as well as develop data-driven policies to shape Boko Haram’s behavior and reduce attacks by them. This book also identifies conditions that predict sexual violence, suicide bombings and attempted bombings, abduction, arson, looting, and targeting of government officials and security installations.?.After reducing Boko Haram’s history to a spreadsheet containing monthly information about different types of attacks and different circumstances prevailing over a 9 year period, this book introduces Temporal Probabilistic (TP) rules that can be automatically learned from data and are easy to explain to policy makers and security experts. This book additionally reports on over 1 year of forecasts made using the model in order to validate predictive accuracy. It also introduces a policy computation method to rein in Boko Haram’s attacks..Applied machine learning researchers, machine learning experts and predictive modeling experts agree that this book is a valuable learning asset. Counter-terrorism ex | | Pindex | Book 2021 |
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