Ontology Learning for the Semantic Web (The Kluwer International Series in Engineering and Computer Science, Volume 665)

Author: Alexander Maedche
Edition: 2002
Binding: Hardcover
ISBN: 0792376560

Ontology Learning for the Semantic Web (The Kluwer International Series in Engineering and Computer Science, Volume 665) (The Springer International Series in Engineering and Computer Science)

Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc. Get Ontology Learning for the Semantic Web (The Kluwer International Series in Engineering and Computer Science, Volume 665) computer books for free.
, 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 Check Ontology Learning for the Semantic Web (The Kluwer International Series in Engineering and Computer Science, Volume 665) our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

Ontology Learning for the Semantic Web (The Kluwer International Series in Engineering and Computer Science, Volume 665) Free

, 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 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

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