| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2006: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2005: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2004: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Research Abstract |
As theoretical viewpoints, we proposed the following models, and implemented the programs of these models with the statistical language S. In order to verify proposed methodology, we made case studies about care service evaluation data, POS (Point Of Sales) data with customer ID and Web access log data. In addition, we participated in the data analysis competition sponsored by the Operations Research Society of Japan etc..
1, We consider methods to extract types of individuals which have multivariate history. We use SOM (Self-Organizing Maps) to extract basic types of individuals at a specified point in time. Next, we define new distances between distributions of basic types on the SOM map using distribution functions. We then map the distributions of behavior types in order to obtain customer types over the long-term by SOM (Seki, et al. 2006). In addition, we consider a method to make index using spatial statistics.
2, We propose models which extract nonlinear structural changes in heterogeneous time series.
(1) We propose a model merge method, in order to obtain a segmentation whose segment has a homogeneous functional relation between variates.
(2) We generalize the SOM when there are two variable groups. We propose two stage SOM, which retains each structure of two variable groups, and extracts types of individuals.
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