Neural Network-Based Methods
Learn about neural network-based knowledge graph embedding methods.
There are several studies on using artificial neural networks to generate knowledge graph embedding methods. Let's take a look at some of the methods.
Semantic matching energy (SME)
This algorithm defines an energy function that is used to assign a value to the triple using neural networks.
The idea here is to extract important components from the entities and put them in a space where they can be compared. In the figure above, the head, relation, and tail are represented in the embedding space using vectors. Then, to capture the connection between the head, tail, and relation, we use projection matrices ("M").
For instance, consider the triple (,,). First, we map the entities and relation to an embedding, say , , and ...