Generative Adversarial Networks are used for generating the data using a...
Machine learning with Semantic Web ontologies follows several strategies...
Several approaches have been developed that generate embeddings for
Desc...
Knowledge graphs and ontologies are becoming increasingly important as
t...
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been...
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been...
Most real-world knowledge graphs (KG) are far from complete and
comprehe...
Many ontologies, in particular in the biomedical domain, are based on th...
In natural language processing, relation extraction seeks to rationally
...
An embedding is a function that maps entities from one algebraic structu...
Motivation: Ontologies are widely used in biology for data annotation,
i...
We propose the Onto2Vec method, an approach to learn feature vectors for...
Applied ontology is a relatively new field which aims to apply theories ...