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Found 3 papers, 3 papers with code
Enhancing Geometric Ontology Embeddings for $\mathcal{EL}^{++}$ with Negative Sampling and Deductive Closure Filtering
Ontology embeddings map classes, relations, and individuals in ontologies into $\mathbb{R}^n$, and within $\mathbb{R}^n$ similarity between entities can be computed or new axioms inferred.
Lattice-preserving $\mathcal{ALC}$ ontology embeddings
Generating vector representations (embeddings) of OWL ontologies is a growing task due to its applications in predicting missing facts and knowledge-enhanced learning in fields such as bioinformatics.
From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddings
Several approaches have been developed that generate embeddings for Description Logic ontologies and use these embeddings in machine learning.
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