Open AccessJournal Article
DL-Learner: Learning Concepts in Description Logics
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TLDR
DL-Learner is a framework for learning in description logics and OWL, a cross-platform framework implemented in Java that allows easy programmatic access and provides a command line interface, a graphical interface as well as a WSDL-based web service.Abstract:
In this paper, we introduce DL-Learner, a framework for learning in description logics and OWL. OWL is the official W3C standard ontology language for the Semantic Web. Concepts in this language can be learned for constructing and maintaining OWL ontologies or for solving problems similar to those in Inductive Logic Programming. DL-Learner includes several learning algorithms, support for different OWL formats, reasoner interfaces, and learning problems. It is a cross-platform framework implemented in Java. The framework allows easy programmatic access and provides a command line interface, a graphical interface as well as a WSDL-based web service.read more
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References
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BookDOI
The Description Logic Handbook: Theory, Implementation and Applications
TL;DR: The Description Logic Handbook as mentioned in this paper provides a thorough account of the subject, covering all aspects of research in this field, namely: theory, implementation, and applications, and can also be used for self-study or as a reference for knowledge representation and artificial intelligence courses.
Book
The Description Logic Handbook
TL;DR: This introduction presents the main motivations for the development of Description Logics as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition.
Book
Ontology Learning from Text: Methods, Evaluation and Applications
TL;DR: This volume presents current research in ontology learning, addressing three perspectives, including methodologies that have been proposed to automatically extract information from texts and to give a structured organization to such knowledge, including approaches based on machine learning techniques.
Book ChapterDOI
A Refinement Operator for Description Logics
TL;DR: In this article, a complete and proper refinement operator for the ALER description logic has been constructed, and it has been shown that all refinement steps for ALER cannot be locally finite, except the ones that introduce the ⊥ concept.
Book ChapterDOI
A refinement operator based learning algorithm for the ALC description logic
Jens Lehmann,Pascal Hitzler +1 more
TL;DR: This paper provides the first learning algorithm based on refinement operators for the most fundamental description logic ALC, and develops the algorithm from thorough theoretical foundations and reports on a prototype implementation.