Method and system for relation learning by multi-hop attention graph neural network

A method comprising:

• providing, by a computing device, an incomplete knowledge graph comprising a plurality of nodes and a plurality of edges, each of the edges connecting two of the plurality of nodes;
• calculating, by the computing device, an attention matrix of the incomplete knowledge graph based on one-hop attention between any two of the plurality of the nodes that are connected by one of the plurality of the edges;
• calculating, by the computing device, multi-head diffusion attention for any two of the plurality of nodes from the attention matrix;
• obtaining, by the computing device, updated embedding of the incomplete knowledge graph using the multi-head diffusion attention;
• and
• updating, by the computing device, the incomplete knowledge graph to obtain updated knowledge graph based on the updated embedding.

A non-transitory computer readable medium storing computer executable code, wherein the computer executable code, when executed at a processor of an active computing device, is configured to:

• provide an incomplete knowledge graph comprising a plurality of nodes and a plurality of edges, each of the edges connecting two of the plurality of nodes;
• calculate an attention matrix of the incomplete knowledge graph based on one-hop attention between any two of the plurality of the nodes that are connected by one of the plurality of the edges;
• calculate multi-head diffusion attention for any two of the plurality of nodes from the attention matrix;
• obtain updated embedding of the incomplete knowledge graph using the multi-head diffusion attention;
• and
• update the incomplete knowledge graph to obtain updated knowledge graph based on the updated embedding.