Temporal Probabilistic Rules and Policy Computation Algorithms
In this chapter, we briefly describe the science underlying the temporal probabilistic (TP) rule paradigm for explaining the behavior of terrorist groups such as Boko Haram. We present the syntax and semantics of TP-rules informally, together with a brief
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V. S. Subrahmanian Chiara Pulice James F. Brown Jacob Bonen-Clark Foreword by
Geert Kuiper
A Machine Learning Based Model of Boko Haram
Terrorism, Security, and Computation Series Editor V. S. Subrahmanian Department of Computer Science and Institute for Security, Technology and Society, Dartmouth College, Hanover, NH, USA
The purpose of the Computation and International Security book series is to establish the state of the art and set the course for future research in computational approaches to international security. The scope of this series is broad and aims to look at computational research that addresses topics in counter-terrorism, counterdrug, transnational crime, homeland security, cyber-crime, public policy, international conflict, and stability of nations. Computational research areas that interact with these topics include (but are not restricted to) research in databases, machine learning, data mining, planning, artificial intelligence, operations research, mathematics, network analysis, social networks, computer vision, computer security, biometrics, forecasting, and statistical modeling. The series serves as a central source of reference for information and communications technology that addresses topics related to international security. The series aims to publish thorough and cohesive studies on specific topics in international security that have a computational and/or mathematical theme, as well as works that are larger in scope than survey articles and that will contain more detailed background information. The series also provides a single point of coverage of advanced and timely topics and a forum for topics that may not have reached a level of maturity to warrant a comprehensive textbook More information about this series at http://www.springer.com/series/11955
V. S. Subrahmanian • Chiara Pulice James F. Brown • Jacob Bonen-Clark
A Machine Learning Based Model of Boko Haram Foreword by Geert Kuiper
V. S. Subrahmanian Department of Computer Science Dartmouth College Hanover, NH, USA
Chiara Pulice Department of Computer Science Dartmouth College Hanover, NH, USA
James F. Brown Department of Computer Science Dartmouth College Hanover, NH, USA
Jacob Bonen-Clark Institute for Advanced Computer Studies University of Maryland, College Park Maryland, MD, USA
ISSN 2197-8778 ISSN 2197-8786 (electronic) Terrorism, Security, and Computation ISBN 978-3-030-60613-8 ISBN 978-3-030-60614-5 (eBook) https://doi.org/10.1007/978-3-030-60614-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or her
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