| Budget Amount *help |
¥11,440,000 (Direct Cost: ¥8,800,000、Indirect Cost: ¥2,640,000)
Fiscal Year 2015: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2014: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2013: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2012: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
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| Outline of Final Research Achievements |
As the foundation of knowledge discovery based on embedding and dimension reduction in high-dimensional feature space, this research characterizes mathematically a Tai mapping hierarchy consisting of mappings that provide the variations of a tree edit distance, analyzes the time complexity of computing their variations and provides the several results concerned with the hierarchy. Also this research designs and implements the fastest feature selection algorithms Super-CWC and Super-LCC based on consistency in categorical data. Furthermore, this research proposes the similarity search method in high-dimensional feature space based on Hilbert sorting.
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