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BUILDING A DATA-MINING GRID FOR MULTIPLE HUMAN BRAIN DATA ANALYSIS
Authors:Ning  Zhong   Jia  Hu   Shinichi  Motomura   Jing-Long  Wu   Chunnian  Liu
Affiliation:Department of Information Engineering, Maebashi Institute of Technology Maebashi-City, Japan; Department of Intelligent Mechanical Systems, Kagawa University, Takamatsu City, Kagawa, Japan; College of Computer Science, Beijing University of Technology, Beijing, China
Abstract:E-science is about global collaboration in key areas of science such as cognitive science and brain science, and the next generation of infrastructure such as the Wisdom Web and Knowledge Grids. As a case study, we investigate human multiperception mechanism by cooperatively using various psychological experiments, physiological measurements, and data mining techniques for developing artificial systems which match human ability in specific aspects. In particular, we observe fMRI (functional magnetic resonance imaging) and EEG (electroencephalogram) brain activations from the viewpoint of peculiarity oriented mining and propose a way of peculiarity oriented mining for knowledge discovery in multiple human brain data. Based on such experience and needs, we concentrate on the architectural aspect of a brain-informatics portal from the perspective of the Wisdom Web and Knowledge Grids. We describe how to build a data-mining grid on the Wisdom Web for multiaspect human brain data analysis. The proposed methodology attempts to change the perspective of cognitive scientists from a single type of experimental data analysis toward a holistic view at a long-term, global field of vision.
Keywords:the data-mining grid    the Wisdom Web    peculiarity oriented mining    brain-informatics portals    multiaspect human brain data analysis
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