Ontology Learning for the Semantic Web

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Ontology Learning for the Semantic Web (2001)

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by Er Maedche , Steffen Staab

Venue:	IEEE Intelligent Systems
Citations:	492 - 16 self

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@ARTICLE{Maedche01ontologylearning,
    author = {Er Maedche and Steffen Staab},
    title = {Ontology Learning for the Semantic Web},
    journal = {IEEE Intelligent Systems},
    year = {2001},
    volume = {16},
    pages = {72--79}
}

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Abstract

The Semantic Web relies heavily on the formal ontologies that structure underlying data for the purpose of comprehensive and transportable machine understanding. Therefore, the success of the Semantic Web depends strongly on the proliferation of ontologies, which requires fast and easy engineering of ontologies and avoidance of a knowledge acquisition bottleneck. Ontology Learning greatly facilitates the construction of ontologies by the ontology engineer. The vision of ontology learning that we propose here includes a number of complementary disciplines that feed on different types of unstructured, semi-structured and fully structured data in order to support a semi-automatic, cooperative ontology engineering process. Our ontology learning framework proceeds through ontology import, extraction, pruning, refinement, and evaluation giving the ontology engineer a wealth of coordinated tools for ontology modeling. Besides of the general framework and architecture, we show in this paper some exemplary techniques in the ontology learning cycle that we have implemented in our ontology learning environment, Text-To-Onto, such as ontology learning from free text, from dictionaries, or from legacy ontologies, and refer to some others that need to complement the complete architecture, such as reverse engineering

Keyphrases

semantic web ontology learning exemplary technique general framework free text easy engineering complementary discipline knowledge acquisition bottleneck different type ontology import transportable machine understanding cooperative ontology engineering process reverse engineering ontology modeling complete architecture formal ontology ontology engineer coordinated tool legacy ontology framework proceeds

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