Classification-based collaborative filtering using market basket data
페이지 정보
조회 1,322회 작성일 20-12-08 17:12
본문
| Journal | Expert Systems with Applications, 29(3), 700-704. |
|---|---|
| Name | Lee, J.-S., Jun, C.-H., Lee, J., and Kim, S. |
| Year | 2005 |
Collaborative filtering based on voting scores has been known to be the most successful recommendation technique and has been used in a number of different applications. However, since voting scores are not easily available, similar techniques should be needed for the market basket data in the form of binary user-item matrix. We viewed this problem as a two-class classification problem and proposed a new recommendation scheme using binary logistic regression models applied to binary user-item data. We also suggested using principal components as predictor variables in these models. The proposed scheme was illustrated with a numerical experiment, where it was shown to outperform the existing one in terms of recommendation precision in a blind test.