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English(EN) Temporal Heterogeneous Graph Transformer for Credit Card Fraud Detection

新的时间图Transformer旨在改进信用卡欺诈检测

研究人员开发了THGT-FD,一种用于信用卡欺诈检测的时间异构图Transformer。该模型使用交易本身和六种关系类型的token来表示交易,并结合了Time2Vec编码。在一个大型数据集上的实验表明,THGT-FD的AUC-ROC为0.8536,尽管基于直方图的梯度提升基线表现稍好,AUC-ROC为0.8722。研究表明,关系信息对于欺诈风险评估是有价值的。 AI

影响 引入了一种新颖的基于图的方法,可以提高欺诈检测系统的准确性。

排序理由 该集群包含一篇详细介绍特定任务新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的时间图Transformer旨在改进信用卡欺诈检测

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该集群包含一篇详细介绍特定任务新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Qinwen Yan ·

    用于信用卡欺诈检测的时间异构图Transformer

    arXiv:2609.07100v1 Announce Type: cross Abstract: Credit card fraud detection typically relies on tabular features, while repeated attributes can also provide useful relational signals. This paper proposes THGT-FD, a Temporal Heterogeneous Graph Transformer for Fraud Detection. E…