Knowledge graphs are multi-relation heterogeneous graphs. Thus, the existence of numerous multi-relation entities imposes a tough challenge to the modelling of the knowledge graph. Some recent works represent the property of corresponding entities and relations by generating embeddings. They attempted to identify the missing entities by translation operations or semantic matching. However, the expressiveness of these approaches depends on the entity (relations) embedding. The heterogeneity of entities leads to the difficulty of balancing uniform embedding dimension settings on complex and spar...
