End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

A method for knowledge base completion includes encoding a knowledge base comprising entities and relations between the entities into embeddings for the entities and embeddings for the relations. The embeddings for the entities are encoded based on a Graph Convolutional Network (GCN) with different weights for at least some different types of the relations, which GCN is called a Weighted GCN (WGCN). The method further includes decoding the embeddings by a convolutional network for relation prediction. The convolutional network is configured to apply one dimensional (1D) convolutional filters on the embeddings, which convolutional network is called Conv-TransE. The method further includes at least partially complete the knowledge base based on the relation prediction.

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