TransE

Definition

Translating embeddings (TransE) is a Knowledge Graph embedding method. TransE represents entities and relations as vectors in the same low-dimensional space. The model is trained through Contrastive Learning.

For a triplet $⟨h,r,t⟩$, let $\mathbf{h},\mathbf{r},\mathbf{t}\in {\mathbb{R}}^d$ be embedding vectors. The objective of TransE is finding the vectors satisfying the equality $\mathbf{h}+\mathbf{r}=\mathbf{t}$

The entity score function is defined as $f_r(h,t)=-||\mathbf{h}+\mathbf{r}-\mathbf{t}||$

TransE cannot model symmetric and 1-to-N relations