AAAI 2024technical0 citations
Neuro-Symbolic Integration for Reasoning and Learning on Knowledge Graphs
Abstract
The goal of this thesis is to address knowledge graph completion tasks using neuro-symbolic methods. Neuro-symbolic methods allow the joint utilization of symbolic information defined as meta-rules in ontologies and knowledge graph embedding methods that represent entities and relations of the graph in a low-dimensional vector space. This approach has the potential to improve the resolution of knowledge graph completion tasks in terms of reliability, interpretability, data-efficiency and robustness.
BibTeX
@article{Werner_2024, title={Neuro-Symbolic Integration for Reasoning and Learning on Knowledge Graphs}, volume={38}, url={https://ojs.aaai.org/index.php/AAAI/article/view/30415}, DOI={10.1609/aaai.v38i21.30415}, abstractNote={The goal of this thesis is to address knowledge graph completion tasks using neuro-symbolic methods. Neuro-symbolic methods allow the joint utilization of symbolic information defined as meta-rules in ontologies and knowledge graph embedding methods that represent entities and relations of the graph in a low-dimensional vector space. This approach has the potential to improve the resolution of knowledge graph completion tasks in terms of reliability, interpretability, data-efficiency and robustness.}, number={21}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Werner, Luisa}, year={2024}, month={Mar.}, pages={23429-23430} }