揭露印度恐怖主义网络的机器学习方法

Anchal Hora, Asmita Bari, Sonal Rawat
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引用次数: 2

摘要

恐怖主义是社会上普遍存在的巨大威胁,已经存在了几个世纪。由于无法解释的原因,一些恐怖袭击往往比其他袭击更能引起共鸣。这是世界各国面临的最大危险之一。过去曾多次尝试消灭恐怖主义,但需要一些有前途的替代技术来消除恐怖主义造成的巨大损失。因此,本文的作者通过应用不同的机器学习算法设计了各种方法,并试图通过视觉分析来识别恐怖事件和网络中隐藏的模式和趋势,从而将结果可视化。这项工作完全是通过对恐怖主义数据库的可视化分析来描述的,该数据库进一步预测了印度这些袭击的未来结果。
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Machine Learning Approaches to Uncover Terrorism Network in India
Terrorism is a great threat prevailing in the society and has been around for centuries. Some terror strikes tend to resonate more than others, for reasons that are inexplicable. It is one of the biggest danger faced by countries all over the world. Several attempts were made to exterminate terrorism in the past but there is a need for some alternative promising techniques to eradicate the immense loss caused due to terrorism. Therefore, authors of this paper have devised various approaches by applying different machine learning algorithms and tried to visualize the result through visual analytics that recognize hidden patterns and trends in terrorist events and networks. This work is entirely depicted through visual analytics on terrorism database which further predicting the future outcome of these attacks in India.
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