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Abstract

The Semantic Web relies heavily on the formal ontologies that structure its underlying data for comprehensive and transportable machine understanding. Ontology learning greatly facilitates the construction of ontologies. The authors' view of ontology learning includes a number of complementary disciplines that feed on different types of unstructured, semistructured, and fully structured data to support semiautomatic, cooperative ontology engineering. In addition to discussing their general ontology-learning framework and architecture, the authors give examples of the ontology-learning cycle that they have implemented in their ontology-learning environment, Text-To-Onto, such as ontology learning from free text, dictionaries, or legacy ontologies.

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Ontology Learning for the Semantic Web

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maedche2001ontology
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