Title :
A hierarchical distributed data mining architecture
Author :
Liu, Bin ; Cao, Shu-gui ; Li, Qing-chun ; Li, Qi
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Abstract :
Current distributed data mining (DDM) systems popularly assume distributed data sources as partitions of a virtual data table and separately mine them. In fact, when there is essential difference among data sources, the assumption will fail and DDM result quality will also be damaged. For this issue, a hierarchical DDM architecture is proposed by grouping data sources according to their similarity. Ontology technology is adopted to depict the essential content of data sources and measure their similarity.
Keywords :
collections of physical data; data mining; distributed processing; DDM systems; current distributed data mining; distributed data sources; hierarchical distributed data mining architecture; ontology technology; virtual data table; Computer architecture; Cybernetics; Data mining; Data models; Delta modulation; Machine learning; Ontologies; Distributed data mining; hierarchical architecture; ontology;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016720
