Distributed graph embedding-based federated graph clustering method, apparatus, and readable storage medium

Abstract

Provided are a federated graph clustering method based on distributed graph embedding, a device, and a readable storage medium. The method comprises: constructing a first graph on the basis of first party data, and constructing a second graph on the basis of second party data; performing an encrypted intersection on the first party data and the second party data, determining common nodes in the first graph and the second graph, and associating the first graph with the second graph according to the common nodes to obtain a federated graph; learning on the federated graph by using a random walk-based distributed graph embedding algorithm, and determining a first graph embedding vector [PiA, PiB] starting from the first graph and a second graph embedding vector [PiA', PiB′] starting from the second graph; and performing a clustering analysis on the first graph embedding vector [PiA, PiB] and the second graph embedding vector [PiA′, PiB′] of the federated graph on the basis of a federated clustering method to obtain a clustering result. By utilizing the present method, federated graph clustering can be carried out on private data of two parties, and a better clustering effect is obtained.