Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding
Table 3: Results of knowledge graph completion (FB24K)
['Metric', 'Entity Predication Hits@10', 'Entity Predication Hits@10', 'Entity Predication Mean Rank', 'Entity Predication Mean Rank', 'Relation Predication Hits@1', 'Relation Predication Hits@1', 'Relation Predication Mean Rank', 'Relation Predication Mean Rank']
This results indicates that KANE still outperforms other baselines significantly and consistently. This also verifies the necessity of modeling high-order structural and attribute information of KGs in Knowledge graph embedding models.