文件名称:
Fraud Detection Machine Learning
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文件大小: 9mb
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上传时间: 2018-02-26
详细说明： 基于非监督学习的欺诈识别 摘要： Fraud is a threat that most online service providers must address in the development of their systems to ensure an efficient security policy and the integrity of their revenue. Amadeus, a Global Distribution System providing a trans- action platform for flight booking by travel agents, is tar- geted by fraud attempts that could lead to revenue losses and indemnifications. The objective of this thesis is to detect fraud attempts by applying machine learning algorithms to bookings repre- sented by Passenger Name R ecord history. Due to the lack of labelled data, the current study presents a benchmark of unsupervised algorithms and aggregation methods. It also describes anomaly detection techniques which can be applied to self-organizing maps and hierarchical clustering. Considering the important amount of transactions per second processed by Amadeus back-ends, we eventually highlight potential bottlenecks and alternatives. ...展开收缩
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