Distributed Knowledge Acquisition Based on Semantic Grid
Huimin Wang, Guihua Nie, Kui Fu · 2009
Today, many public organizations, industries, and scientific labs produce and manage large amounts of complex data and information that are distributed and semantically heterogeneous. Knowledge acquisition from distributed data resources to support decision making is receiving an increasing attention. The paper proposes a distributed knowledge acquisition architecture and puts forward any new solve algorithms for knowledge acquisition from large-scale distributed and heterogeneous data resources. Semantic web technology is used to explicitly define data semantics. By the semantic mapping between data resources and ontology, the query and acquisition of user-demanded knowledge can be realized by distributed data mining and semantic reasoning.