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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