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NEURAL NETWORK SYSTEM AND METHOD FOR ANALYZING RELATIONSHIP NETWORK GRAPH

机译:神经网络系统和关系网络图分析方法

摘要

Disclosed are a neural network system and method executed by means of a computer and used for analyzing a relationship network graph. The neural network system comprises: a feature extraction layer (21) for extracting a feature vector of a node in a relationship network graph; a deep neural network (22) for carrying out first processing on the feature vector, so as to obtain a first output; a graph neural network (23) for carrying out second processing on the feature vector in combination with adjacency information of the relationship network graph, so as to obtain a second output, wherein the adjacency information is used for representing connection relationships between various nodes included in the relationship network graph; and a fusion layer (24) for fusing the first output and the second output, and outputting, based on a fusion result, a prediction result regarding the node.
机译:公开了一种通过计算机执行并用于分析关系网络图的神经网络系统和方法。该神经网络系统包括:特征提取层(21),用于提取关系网络图中的节点的特征向量;以及深度神经网络(22),用于对特征向量进行第一处理,以获得第一输出;图神经网络(23),用于结合关系网络图的邻接信息对特征向量进行第二处理,以获得第二输出,其中,邻接信息用于表示包含在各个节点之间的连接关系关系网络图;融合层(24),用于融合第一输出和第二输出,并基于融合结果输出关于节点的预测结果。

著录项

  • 公开/公告号WO2020114122A1

    专利类型

  • 公开/公告日2020-06-11

    原文格式PDF

  • 申请/专利权人 ALIBABA GROUP HOLDING LIMITED;

    申请/专利号WO2019CN112564

  • 发明设计人 CHANG XIAOFU;SONG LE;

    申请日2019-10-22

  • 分类号G06N3/04;

  • 国家 WO

  • 入库时间 2022-08-21 11:10:53

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