Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web by Alexander Maedche, published by Springer US on October 31, 2012, is a softcover reprint of the original 1st edition from 2002, comprising 244 pages. This book explores techniques for applying knowledge discovery methods to various web data sources, such as HTML documents and dictionaries, to aid in the engineering and maintenance of ontologies.
Readers will find a comprehensive examination of ontology learning that integrates multiple disciplines, utilizing unstructured and semi-structured data to facilitate a semi-automatic ontology engineering process. This work is tailored for researchers and developers in the field of semantic web applications and serves as a valuable supplemental reference for advanced courses focused on ontologies and the semantic web.
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Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process.
Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.
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