Extended resource space model

Authors:
Hai Zhuge;Erlin Yao;Yunpeng Xing;Jie Liu
Affiliations:
Hunan Knowledge Grid Lab, Hunan University of Science and Technology, Hunan, China and China Knowledge Grid Research Group, Key Lab of Intelligent Information Processing, Institute of Computing Te ...;China Knowledge Grid Research Group, Key Lab of Intelligent Information Processing, Institute of Computing Technology Chinese Academy of Sciences, Beijing, China and Graduate School of Chinese Aca ...;China Knowledge Grid Research Group, Key Lab of Intelligent Information Processing, Institute of Computing Technology Chinese Academy of Sciences, Beijing, China and Graduate School of Chinese Aca ...;China Knowledge Grid Research Group, Key Lab of Intelligent Information Processing, Institute of Computing Technology Chinese Academy of Sciences, Beijing, China and Graduate School of Chinese Aca ...
Venue:
Future Generation Computer Systems
Year:
2005

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Abstract

The resource space model (RSM) is a semantic data model based on orthogonal classification semantics for efficiently managing various resources in the future interconnection environment. This paper extends the RSM in theory by formalizing the resource space, investigating its characteristics from the perspective of set theory, defining the resource space schema and developing its normal forms. The topological space properties of the resource space are presented based on the definition of a distance in the space and the construction of a quotient space structure. The proposed theory ensures the RSM to correctly and efficiently specify and manage resources.