挖掘因果关系：对伊斯兰国的数据驱动研究
Mining for Causal Relationships: A Data-Driven Study of the Islamic State
摘要：
伊拉克和沙姆伊斯兰国（ISIS）是在伊拉克和叙利亚活动的主要叛乱组织，在2014年6月接管摩苏尔时声名鹊起。在本文中，我们提出了一种数据驱动的方法来分析这个群体，使用的数据集包括2200起围绕ISIS和反对它的力量（包括伊拉克，叙利亚和美国领导的联盟）的军事活动事件。我们结合逻辑编程和因果推理的思想，挖掘关联规则，我们提出的证据的因果关系。我们提出的关系，伊斯兰国车载简易爆炸装置（VBIED）在叙利亚的活动与伊拉克的军事行动，联军空袭，和伊斯兰国简易爆炸装置的活动，以及规则，可以作为间接火，自杀式袭击和逮捕的峰值指标。
英文摘要：
The Islamic State of Iraq and al-Sham (ISIS) is a dominant insurgent group operating in Iraq and Syria that rose to prominence when it took over Mosul in June, 2014. In this paper, we present a data-driven approach to analyzing this group using a dataset consisting of 2200 incidents of military activity surrounding ISIS and the forces that oppose it (including Iraqi, Syrian, and the American-led coalition). We combine ideas from logic programming and causal reasoning to mine for association rules for which we present evidence of causality. We present relationships that link ISIS vehicle-bourne improvised explosive device (VBIED) activity in Syria with military operations in Iraq, coalition air strikes, and ISIS IED activity, as well as rules that may serve as indicators of spikes in indirect fire, suicide attacks, and arrests.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
