摘要翻译：
本文提出了一种分析恐怖主义灾难背后隐藏的社会网络基础的方法。它是为了解决节点发现问题，即发现一个在社会网络中具有相关功能的节点，但却逃避了对节点存在和相互关系的监控。该方法旨在将专家调查人员的先验认识、复杂图论对恐怖分子社会网络本质的洞察和计算数据处理相结合。利用2001年9/11事件的社会网络进行了仿真实验，对该方法的性能进行了评估。
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英文标题：
《Analyzing covert social network foundation behind terrorism disaster》
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作者：
Yoshiharu Maeno, and Yukio Ohsawa
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最新提交年份：
2007
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  This paper addresses a method to analyze the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory, and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.
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PDF链接：
https://arxiv.org/pdf/0710.4231