지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2005.11
- 수록면
- 271 - 275 (5page)
이용수
이 논문의 연구 히스토리 (2)
2005
Prediction of User's Preference by using Fuzzy Rule & RDB Inference : A Cosmetic Brand Selection
Jin Sung Kim
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2005.12
학술저널
Prediction of User Preferred Cosmetic Brand Based on Unified Fuzzy Rule Inference
Jin Sung Kim
한국지능시스템학회 학술발표 논문집
2005.11
학술대회자료
- 이 논문의 후속연구가 궁금하신가요?
- 연관 학술논문 또는 학술발표를 통해 보다 발전된 연구결과를 확인하실 수 있습니다.
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초록· 키워드
오류제보하기
In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0~1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).
목차
Abstract
1. Introduction
2. Research Methodology
3. Implementation
4. Conclusion
References
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UCI(KEPA) : I410-ECN-0101-2009-028-015025982