Node classification method of heterogeneous information network based on meta-paths

The invention provides a node classification method of a heterogeneous information network based on a meta-path, and relates to the technical field of deep learning and network embedding. The method comprises the following steps: firstly, obtaining all meta-paths in a heterogeneous information network to obtain a meta-path set, and increasing the number of meta-paths between nodes in the obtainedmeta-path set; then determining a feature vector of each meta-path; and finally, obtaining a feature vector representation mode of the nodes in the heterogeneous information network according to the feature vectors obtained by the meta-paths, and classifying the nodes in the meta-paths by using a convolutional neural network. According to the method, the paths between the nodes are obtained through the meta-paths, the heterogeneous information network training process is simplified to a certain extent, and the accuracy of the final classification result is improved. 本发明提供一种基于元路径的异质信息网络的节点分类方法，涉及深度学习与网络嵌入技术领域。该方法首先获取异质