| Project/Area Number |
22730333
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Commerce
|
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2010 – 2011
|
| Project Status |
Completed (Fiscal Year 2011)
|
| Budget Amount *help |
¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | リコメンデーション / システム / リコメンデーション・システム / 選択モデル / MCMC / リコメンデーションシステム / ベイズ統計 / 消費者異質性 |
|---|
| Research Abstract |
In this research we proposed and analyzed a choice model that utilizes two types of data, behavioral and(stated) preference data, in order to improve the accuracy of a recommendation system. We applied the model to videos viewing and preferences data of a particular video-sharing website on the internet. We found that compared with the model that used only behavioral and only preference data, the model that combined both data explained the variation of data and predicted individual decisions much better. This indicates the value of using both data in recommendation system.
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