Graph

Pure mathematics

Chen

Inference

Mathematics

Psychotherapist

Hyperbolic space

Biology

Euclidean geometry

Association (psychology)

Paleontology

Artificial intelligence

Psychology

Hyperbolic geometry

Differential geometry

Geometry

Computer science

Theoretical computer science

Knowledge graph

Embedding

Capturing associations for knowledge graphs (KGs) through entity alignment, entity type inference and other related tasks benefits NLP applications with comprehensive knowledge representations. Recent related methods built on Euclidean embeddings are challenged by the hierarchical structures and different scales of KGs. They also depend on high embedding dimensions to realize enough expressiveness. Differently, we explore with low-dimensional hyperbolic embeddings for knowledge association. We propose a hyperbolic relational graph neural network for KG embedding and capture knowledge associations with a hyperbolic transformation. Extensive experiments on entity alignment and type inference demonstrate the effectiveness and efficiency of our method.

Knowledge Association with Hyperbolic Knowledge Graph Embeddings