Quotation Hashemi, Mahdi, Hall, Margeret. 2018. Visualization, Feature Selection, Deep Learning: Identifying The Responsible Group for Extreme Acts of Violence. IEEE Access.


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Abstract

The toll of human casualties and psychological impacts on societies make any study on violent extremism worthwhile, let alone attempting to detect patterns among them. This paper is an effort to predict which violent extremist organization (VEO), among 14 currently active ones throughout the world, is responsible for a violent act based on 14 features, including its human and structural tolls, its target type and value, intelligence, and weapons utilized in the attack. Three main steps in our paper include: 1) the visualization of the violent acts through linear and non-linear dimensionality reduction techniques; 2) sequential forward feature selection based on the generalization accuracy of three machine learning models-decision tree, and linear and nonlinear SVM; and 3) employing multilayer perceptron to predict the VEO based on the selected features of a violent act. Top-ranked selected features were related to the target type and plan and the multilayer perceptron achieved up to 40% test accuracy.

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Publication's profile

Status of publication Published
Affiliation External
Type of publication Journal article
Journal IEEE Access
Citation Index SCI
Language English
Title Visualization, Feature Selection, Deep Learning: Identifying The Responsible Group for Extreme Acts of Violence
Year 2018
URL https://ieeexplore.ieee.org/document/8520859
DOI http://dx.doi.org/10.1109/ACCESS.2018.2879056
Open Access Y
Open Access Link https://ieeexplore.ieee.org/document/8520859

Associations

People
Hall, Margeret (Details)
External
Hashemi, Mahdi (University of Nebraska at Omaha, United States/USA)
Research areas (Ă–STAT Classification 'Statistik Austria')
1127 Information science (Details)
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