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http://dx.doi.org/10.5391/IJFIS.2005.5.4.353

Prediction of User's Preference by using Fuzzy Rule & RDB Inference: A Cosmetic Brand Selection  

Kim, Jin-Sung (School of Business Administration, Jeonju University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.5, no.4, 2005 , pp. 353-359 More about this Journal
Abstract
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).
Keywords
Cosmetic; Data mining; Expert systems; Fuzzy clustering; Fuzzy rule; Knowledge management; RDB; SQL;
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