Faithful Embeddings for Knowledge Bases
Recently, increasing efforts are put into learning continual representations for symbolic
knowledge bases (KBs). However, these approaches either only embed the data-level …
knowledge bases (KBs). However, these approaches either only embed the data-level …
BoxEL: Concept and Role Box Embeddings for the Description Logic EL++
Description logic (DL) ontologies extend knowledge graphs (KGs) with conceptual
information and logical background knowledge. In recent years, there has been growing …
information and logical background knowledge. In recent years, there has been growing …
Towards semantically enriched embeddings for knowledge graph completion
Embedding based Knowledge Graph (KG) Completion has gained much attention over the
past few years. Most of the current algorithms consider a KG as a multidirectional labeled …
past few years. Most of the current algorithms consider a KG as a multidirectional labeled …
Dual Box Embeddings for the Description Logic EL++
OWL ontologies, whose formal semantics are rooted in Description Logic (DL), have been
widely used for knowledge representation. Similar to Knowledge Graphs (KGs), ontologies …
widely used for knowledge representation. Similar to Knowledge Graphs (KGs), ontologies …
Ontology Embedding: A Survey of Methods, Applications and Resources
Ontologies are widely used for representing domain knowledge and meta data, playing an
increasingly important role in Information Systems, the Semantic Web, Bioinformatics and …
increasingly important role in Information Systems, the Semantic Web, Bioinformatics and …
Neuro-Symbolic RDF and Description Logic Reasoners: The State-Of-The-Art and Challenges
Ontologies are used in various domains, with RDF and OWL being prominent standards for
ontology development. RDF is favored for its simplicity and flexibility, while OWL enables …
ontology development. RDF is favored for its simplicity and flexibility, while OWL enables …
Strong Faithfulness for ELH Ontology Embeddings
V Lacerda, A Ozaki, R Guimarães - arXiv preprint arXiv:2310.02198, 2023 - arxiv.org
Ontology embedding methods are powerful approaches to represent and reason over
structured knowledge in various domains. One advantage of ontology embeddings over …
structured knowledge in various domains. One advantage of ontology embeddings over …
Capturing knowledge graphs and rules with octagon embeddings
V Charpenay, S Schockaert - arXiv preprint arXiv:2401.16270, 2024 - arxiv.org
Region based knowledge graph embeddings represent relations as geometric regions. This
has the advantage that the rules which are captured by the model are made explicit, making …
has the advantage that the rules which are captured by the model are made explicit, making …
A Self-matching Training Method with Annotation Embedding Models for Ontology Subsumption Prediction
Y Shiraishi, K Kaneiwa - arXiv preprint arXiv:2402.16278, 2024 - arxiv.org
Recently, ontology embeddings representing entities in a low-dimensional space have been
proposed for ontology completion. However, the ontology embeddings for concept …
proposed for ontology completion. However, the ontology embeddings for concept …
Knowledge Base Embeddings: Semantics and Theoretical Properties
C Bourgaux, R Guimarães, R Koudijs… - arXiv preprint arXiv …, 2024 - arxiv.org
Research on knowledge graph embeddings has recently evolved into knowledge base
embeddings, where the goal is not only to map facts into vector spaces but also constrain …
embeddings, where the goal is not only to map facts into vector spaces but also constrain …