9780792376569 - Ontology Learning for the Semantic Web (The Springer International Series in Engineering and Computer Science, 665, Band 665) von Maedche, Alexander (3 Ergebnisse)

Buch. Zustand: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.

Zustand: New. Explores techniques for applying knowledge discovery techniques to different web data sources, such as HTML documents, dictionaries, and more, in order to support the task of engineering and maintaining ontologies. This work is useful for researchers and developers of semantic web applications. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 244 pages, biography. BIC Classification: UM; UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 242 x 166 x 20. Weight in Grams: 552. . 2002. Hardback. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.