Before revision: The use of deep learning for knowledge graph embedding has shown good predictive performance even if they are more expensive in the training phase, angry of data , and often required a pre-trained embedding representation of knowledge graph coming from a different embedding model.
After revision: The use of deep learning for knowledge graph embedding has shown good predictive performance even if they are more expensive in the training phase, data-hungry , and often required a pre-trained embedding representation of knowledge graph coming from a different embedding model.