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neuro-symbolic methods

Neuro-symbolic methods for Semantic Web ontologies

Robert Hoehndorf, Associate Professor, Computer Science
Sep 18, 11:30 - 12:30

B9 L2 H2 H2

Semantic web Ontologies neuro-symbolic methods

Semantic Web ontologies are widely used to provide a conceptual schema for sharing and integrating data and knowledge using a logic-based language. The content of ontologies may also be used to provide background knowledge in machine learning models or provide domain-specific constraints that can be verified automatically and used for zero-shot predictions. The combination of embedding symbolic representations (such as ontologies) and extracting symbolic representations from the embeddings are two main components of neuro-symbolic AI systems. I will introduce methods for embedding Semantic Web ontologies and outline some of the properties of the embeddings that relate to model and proof theory.

Robert Hoehndorf

Associate Professor, Computer Science

artificial intelligence bioinformatics biomedical data knowledge representation Neuro-Symbolic AI neuro-symbolic methods

Robert Hoehndorf is an Associate Professor of Computer Science at KAUST. His research focuses on bioinformatics, knowledge representation and reasoning, Semantic Web technologies, and neuro-symbolic methods.

Computer Science (CS)

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