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The Status Quo of Ontology Learning from Unstructured Knowledge Sources for Knowledge Management

Abstract : In the global race for competitive advantage Knowledge Management gains increasing importance for companies. The purposeful and systematic creation, maintenance, and transfer of unstructured knowledge sources demands for advanced Information Technology. Ontologies constitute a basic ingredient of Knowledge Management; thus, ontology learning from unstructured knowledge sources is of particular interest since it bears the potential to bring significant advantages for Knowledge Management. This paper presents a study of state-of-the-art research of ontology learning from unstructured knowledge sources for Knowledge Management. Nine approaches for ontology learning from unstructured knowledge sources are identified from a systematic review of literature. A six point classification framework is developed. The review results are analyzed, synthesized, and discussed to give an account of the current state-of-the-art for contributing to an enhanced understanding of ontology learning from unstructured knowledge sources for Knowledge Management.
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Andreas Scheuermann, Jens Obermann. The Status Quo of Ontology Learning from Unstructured Knowledge Sources for Knowledge Management. 1st IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM), Aug 2012, Montpellier, France. pp.72-94, ⟨10.1007/978-3-642-54897-0_5⟩. ⟨hal-01256586⟩

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