| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Outline of Final Research Achievements |
In this study, we proposed a new approach for Kansei data analysis based on rough set-based interrelationship mining. We firstly proposed the concept of the interrelationship mining that enables us to extract characteristics based on comparison of attribute values between different attributes. In the interrelationship mining, the relationship between attribute values are explicitly described by newly introduced attributes called interrelated attributes. Addition of the interrelated attributes for the interrelationship mining causes increase of the number of attributes. We then constructed rough set-based attribute reduction systems for datasets with many objects and attributes. We also discussed to apply the rough set-based interrelationship mining to Kansei data analysis. Consequently, our study contributed to provide a new approach for rough set-based Kansei data analysis.
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