RotatE
2000년 도입 · 논문 29편에서 사용
RotatE is a method for generating graph embeddings which is able to model and infer various relation patterns including: symmetry/antisymmetry, inversion, and composition. Specifically, the RotatE model defines each relation as a rotation from the source entity to the target entity in the complex vector space. The RotatE model is trained using a self-adversarial negative sampling technique.
출처: RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
소개 논문: RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Graph Embeddings · Graphs