基于社会网络分析的汽车保险欺诈检测专家系统
An expert system for detecting automobile insurance fraud using social network analysis
摘要：
本文提出了一个专家系统检测，并随后进行调查，汽车保险诈骗集团的合作。该系统进行了详细的描述和检查，在检测欺诈的几个技术难点也被认为是它在实践中是适用的。与许多其他方法相反，该系统使用网络来表示数据。网络是这种关系域最自然的表示，允许制定和分析实体之间的复杂关系。欺诈实体发现采用一种新的评估算法，\textit{Iterative Assessment Algorithm}（\textit{IAA}），也在文章中提出。除了实体的内在属性外，该算法还探索实体之间的关系。原型进行了评估，并严格分析了现实世界的数据。结果表明，汽车保险欺诈可以有效地检测所提出的系统和适当的数据表示是至关重要的。
英文摘要：
The article proposes an expert system for detection, and subsequent investigation, of groups of collaborating automobile insurance fraudsters. The system is described and examined in great detail, several technical difficulties in detecting fraud are also considered, for it to be applicable in practice. Opposed to many other approaches, the system uses networks for representation of data. Networks are the most natural representation of such a relational domain, allowing formulation and analysis of complex relations between entities. Fraudulent entities are found by employing a novel assessment algorithm, \textit{Iterative Assessment Algorithm} (\textit{IAA}), also presented in the article. Besides intrinsic attributes of entities, the algorithm explores also the relations between entities. The prototype was evaluated and rigorously analyzed on real world data. Results show that automobile insurance fraud can be efficiently detected with the proposed system and that appropriate data representation is vital.
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。
