AEP: Aligning knowledge graphs via embedding propagation

Knowledge graph alignment aims to identify entity pairs having the same meaning between different knowledge graphs, which is essential to the automated construction of a coherent knowledge base. With the development of knowledge representation learning, researchers have proposed several useful embedding-based alignment methods. In practice, some entities are easily aligned with high confidence while others are not. However, there is a lack of effective methods which boost the alignment of implicitly aligned entities based on explicitly aligned ones. This paper presents AEP, which combines several effective schemes for accurate knowledge graph alignment. First, we employ a word-embedding model to encode the