| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Outline of Final Research Achievements |
The objective of this study is to develop next-generation pattern recognition methods for management decision making and marketing technology through the analysis of user behaviors based on large-scale log data accumulated in databases such as EC sites. While analyzing actual user behavior history data, we studied new models and methods which are theoretically considered highly versatile. In particular, we developed a machine learning model for developing the issuing logic for real-time coupon ticket systems from multiple viewpoints on users' page browsing behaviors on an EC site. The performances of our proposed models and analytical techniques were verified by using actual data and various applications were demonstrated.
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