Relational peculiarity-oriented mining
Data Mining and Knowledge Discovery
WI based multi-aspect data analysis in a brain informatics portal
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
Multi-aspect data analysis in brain informatics
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Towards human-level web intelligence
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
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In order to investigate the structure of advanced human brain activities, various brain analysis methods are required. It has been observed that multiple brain data such as fMRI brain images and EEG brain waves extracted from human multi-perception mechanism involved in a particular task are peculiar ones with respect to the specific state or the relatedpart of a stimulus. Based on this point of view, we propose a way of peculiarity oriented mining for multi-aspect analysis in multiple human brain data, without using conventional image processing to fMRI brain images and frequency analysis to brain waves. The proposed approach provides a new wayfor automatic analysis and understanding of human brain data to replace human-expert centric visualization. We attempt to change the perspective of cognitive scientists from a single type of experimental data analysis towards a holistic view.