Method and Device for Distributed Graph Embedding

Abstract

The embodiment of the invention provides a method and a device for embedding a relation network graph in a multi-dimensional space through a distributed architecture. The distributed architecture comprises a plurality of processing devices, wherein one set of nodes of the relation network graph is distributed to each processing device. The method is executed by a certain processing device, and comprises the steps of: determining first-order adjacent nodes of a first node for which the processing device is responsible, determining processing devices corresponding to the first-order adjacent nodes; determining an initial embedding vector of the first node as a current order embedding vector; employing the current order embedding vector of the first-order adjacent nodes to calculate the nextorder embedding vector of the first node, and employing the next order embedding vector to update the current order embedding vector; and continuously executing the updating step until the current order quantity reaches a preset search depth, and taking the current order embedding vector at present as an embedding vector of the multi-dimensional space. Therefore, the distributed graph embedding method and device can effectively embed the relation network graph into the multi-dimensional space.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer information processing, and in particular to a method and device for graph embedding using a distributed architecture. Background technique [0002] The relationship network diagram is a description of the relationship between entities in the real world, and is currently widely used in various computer information processing. Generally, a relational network graph includes a set of nodes and a set of edges. Nodes represent entities in the real world, and edges represent connections between entities in the real world. For example, in a social network, people are entities, and relationships or links between people are edges. [0003] In many cases, it is hoped that each node (entity) in the relationship network graph is represented by a vector in a multidimensional space, that is, each node is mapped to a multidimensional space, and the nodes in the graph are represented by poi...

AI Technical Summary

Problems solved by technology

However, in many cases where the graph diameter of the relational network graph is too small and the node search depth is large, the amount of calculation of each processing device is still too large and the load is significantly overloaded, which makes the process of graph embedding difficult to perform efficiently.

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