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http://dx.doi.org/10.5391/JKIIS.2005.15.7.805

Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern  

Lee Hyong-Euk (한국과학기술원 전자전산학과)
Kim Yong-Hwi (한국과학기술원 전자전산학과)
Park Kwang-Hyun (한국과학기술원 전자전산학과)
Kim Yong-Su (대전대학교 컴퓨터 공학부)
June Jin-Woo (한국과학기술원 인간친화복지로봇시스템연구센터)
Cho Joonmyun (한국전자통신연구원 지능로봇연구단)
Kim MinGyoung (한국전자통신연구원 지능로봇연구단)
Bien Z. Zenn (한국과학기술원 전자전산학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.7, 2005 , pp. 805-812 More about this Journal
Abstract
Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.
Keywords
퍼지 귀납 학습;지식 발견;유비쿼터스 환경;행동 패턴 학습;평생 학습;
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  • Reference
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