A Refinement Operator Based Learning Algorithm for the $\mathcal{ALC}$ Description Logic

DOI10.1007/978-3-540-78469-2_17zbMath1136.68490OpenAlexW1850829840MaRDI QIDQ5452088

Pascal Hitzler, Jens Lehmann

Publication date: 28 March 2008

Published in: Inductive Logic Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-78469-2_17

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic in artificial intelligence (68T27) Knowledge representation (68T30)

Related Items (7)

Fuzzy OWL-Boost: learning fuzzy concept inclusions via real-valued boosting ⋮ Mining the semantic web statistical learning for next generation knowledge bases ⋮ Similarity measures over refinement graphs ⋮ Concept learning in description logics using refinement operators ⋮ DL-FOIL Concept Learning in Description Logics ⋮ A Refinement Operator Based Learning Algorithm for the $\mathcal{ALC}$ Description Logic ⋮ Ontology Learning from Interpretations in Lightweight Description Logics

Cites Work

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• Foundations of inductive logic programming
• Pattern Recognition as Rule-Guided Inductive Inference
• Machine Learning: ECML 2004
• A Refinement Operator Based Learning Algorithm for the $\mathcal{ALC}$ Description Logic
• Inductive Logic Programming

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