Network alignment method and device based on iterative depth map learning, and computer equipment

The invention relates to a network alignment method and device based on iterative depth map learning and computer equipment. The method comprises the steps that two network data sets are input into a network alignment model for training until a trained network alignment model for aligning two networks is obtained, the network alignment model comprises an iteration depth map learning network and an alignment prediction network, and the iteration depth map learning network is an iteration depth map learning network; the iterative depth map learning network is used for optimizing a network structure in a network data set to obtain an updated network, the alignment prediction network performs network alignment prediction according to the updated network, and network alignment is performed based on the network alignment model, so that the problem of structural noise existing in an original network is effectively relieved; and the prediction precision of network alignment is improved. 本申请涉及一种基于迭代深度图学习的网络对齐方法、装置及计算机