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GRAPHICAL STRUCTURE MODEL-BASED METHOD, APPARATUS, AND DEVICE FOR CREDIT RISK CONTROL

机译:基于图形结构模型的信用风险控制方法,装置和装置

摘要

A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on an enterprise relationship network that includes nodes and edges. Each labeled sample includes a label indicating whether a corresponding node is a risky credit node. The graphical structure model is configured to iteratively calculate an embedding vector of at least one node in a hidden feature space based on an original feature of the at least one node and/or a feature of an edge associated with the at least one node. An embedding vector corresponding to a test-sample is calculated by using the graphical structure model. Credit risk analysis is performed on the test-sample. The credit risk analysis is performed based on a feature of the test-sample represented in the embedding vector. A node corresponding to the test-sample is labeled as a credit risk node.
机译:获得通过使用标记的样本训练的图形结构模型。基于包括节点和边缘的企业关系网络定义图形结构模型。每个标记的样本包括指示相应节点是否为风险信用节点的标签。图形结构模型被配置为基于至少一个节点的原始特征和/或与至少一个节点相关联的边缘的特征来迭代地计算至少一个节点在隐藏特征空间中的嵌入矢量。通过使用图形结构模型来计算与测试样本相对应的嵌入向量。对测试样本执行信用风险分析。基于嵌入向量中表示的测试样本的特征来执行信用风险分析。对应于测试样本的节点被标记为信用风险节点。

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