摘要
通过对全球恐怖主义数据库(GTD)进行分析,为未来反恐防恐行动提供有价值的信息支持,提出利用大数据挖掘方法对未来反恐态势进行分析。首先采用N-gram模型对原始数据中的motive属性进行挖掘,分析恐怖袭击事件发生的主要动机。其次通过AR自回归模型,对恐袭造成的死亡人数进行预测。最后通过构建TreeMap图,展示未来全球某些重点地区的反恐态势,从恐怖事件发起动机、死亡人数、重点地区3个方面对未来恐怖袭击进行预测。实验结果显示,采用大数据分析预测精度较高。
The analysis of data in the global terrorism database (GTD) can provide reliable and valuable information support for future counter-terrorism and counter-terrorism operations.This paper proposes the method of big data mining to analyze and study the future counter-terrorism situation.First,n-gram model is used to mine motive attributes in original data and analyze the main motivation of terrorist attacks.Secondly,AR autoregressive model was used to predict the death toll caused by terrorist attacks.Finally,TreeMap map was constructed to show the counter-terrorism situation in some key regions of the world in the future.The obtained results are used to predict future terrorist attacks from three aspects:the motivation of terrorist incidents,the number of deaths,and key areas.Experimental results show that the prediction accuracy of big data analysis is relatively high.
作者
冒伟
MAO Wei(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《软件导刊》
2019年第7期28-31,共4页
Software Guide
