Distributed Data Mining Based on Semantic Web and Grid

Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference(2009)

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摘要
Nowadays, the process of data mining is one of the most important topics in scientific and business problems. Grid computing can be used as infrastructures to provide an effective computational support for distributed data mining applications. The paper proposed a data mining architecture from large-scale distributed and semantically heterogeneous data resources in order to efficiently support knowledge acquisition. Grid technology and semantic Web technology were combined to solve the difficult problem of distributed data mining. Data mining in the grid environment can provide highly efficient and powerful data analysis and knowledge discovery solution and semantic Web can effectively solve the heterogeneity of data sources and make them available for data mining.
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关键词
semantically heterogeneous data resource,data source,grid computing,distributed data mining architecture,ontology,data analysis,heterogeneous data resources,distributed data mining,knowledge acquisition,data mining application,grid environment,semantic web,ontologies (artificial intelligence),effective computational support,knowledge discovery,data mining,powerful data analysis,data mining architecture,grid technology,economic forecasting,ontologies,distributed computing,computer architecture,distributed databases,environmental economics
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