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The Web Resource Space Model

Classifying objects into categories at different granularity levels, establishing links between known objects, and discovering clues between known and unknown objects are essential for new-generation semantic data models. This book introduces the Resource Space Model (RSM), which effectively organiz...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Zhuge, Hai (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Web Information Systems Engineering and Internet Technologies Book Series, 4
Temas:
Acceso en línea:Texto Completo
Descripción
Sumario:Classifying objects into categories at different granularity levels, establishing links between known objects, and discovering clues between known and unknown objects are essential for new-generation semantic data models. This book introduces the Resource Space Model (RSM), which effectively organizes and correctly manages resources by normalizing classification semantics. The author, an internationally cited expert in the knowledge grid field, explores these topics: A general methodology of the RSM - the origin, fundamental concepts, characteristics and the development method The relationship between the RSM and the Semantic Link Network, which forms a richer semantic data model to support advanced distributed applications The completeness and necessity theory for query operations of the RSM The algebra and calculus theory for query operations of the RSM The complexity of searching the resource space The physical storage mechanism of the resource space The P2P-based decentralized resource space The probabilistic RSM, which enables users or applications to deal with uncertainty when storing and retrieving resources The Web Resource Space Model represents a major contribution to the field of knowledge grid, offering a highly efficient model for managing e-resources. It is essential reading for researchers of the web, semantic web, and decentralized data engineering.
Descripción Física:XII, 234 p. online resource.
ISBN:9780387727721
ISSN:2627-1761 ;