한국경영과학회:학술대회논문집 (Proceedings of the Korean Operations and Management Science Society Conference)
- 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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- Pages.93-97
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- 2002
전자상거래 개인화 추천을 위한 다차원척도법의 활용
Application of Multidimensional Scaling Method for E-Commerce Personalized Recommendation
- Kim Jong U ;
- Yu Gi Hyeon ;
- Easley Robert F. (Management Department, Mendoza College of Business, University of Notre Dame, USA)
- 발행 : 2002.05.01
초록
In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)
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