Daiji Tanaka

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Privacy preserving data mining is a promising topic for utilizing various personal information without fear of information leaks. Fuzzy co-clustering is a fundamental technique for summarizing mutual cooccurrence information among objects and items, and has been demonstrated to be useful in such applications as document analysis and collaborative filtering.(More)
Semi-supervised clustering is a promising approach for improving partition quality of unsupervised clustering in large-scale data analysis while it is often difficult to utilize an enough amount of supervised objects. A virtual sample approach is a practical technique for improving classification quality in semi-supervised learning, in which additional(More)
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