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双通路图卷积神经网络(DGCN)于2018年提出,它基于半监督学习的两个基本假设:(1).局部一致性:距离比较近的数据,通常有相同的标签;(2).全局一致性:处在相似的上下文中的数据,通常有相同的标签,使用了双通路分别嵌入半监督学习局部一致性与全局一致性的信息,并设计了新的loss函数将二者结合,来对图结构数据进行半监督学习,取得了很好的实验效果。

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