원문정보
A sequential pattern analysis for dynamic discovery of customers' preference
초록
영어
Customers’ needs change every moment. Profitability of stores can’ t be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers’ preference In this study, we propose a recommending procedure using dynamic customers’ preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.
목차
1. 서론
2. 문헌연구
2.1 카테고리 관리(Category Management)
2.2 SOM(Self-organizing map)을 이용한 상품추천
2.3 시간 순서를 고려한 상품추천
3. ㈜더페이스 샵
4. 방법
4.1 전체 분석 프로세스
4.2 매장 판매 프로파일 생성
4.3 SOM을 이용한 매장관리 프로세스
4.4 시간 요인을 고려한 매장 관리 프로세스
4.5 매장별 상품추천프로세스
5. 성능 평가
5.1 실험방법
5.2 실험결과
6. 결론
참고문헌