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dc.contributor.author박지형-
dc.contributor.author이승수-
dc.contributor.author김성주-
dc.contributor.author이석호-
dc.contributor.author염기원-
dc.date.accessioned2024-01-21T02:06:08Z-
dc.date.available2024-01-21T02:06:08Z-
dc.date.created2021-09-06-
dc.date.issued2006-10-
dc.identifier.issn2508-4003-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/135063-
dc.description.abstractThe ubiquitous environment is to support people in their everyday life in an inconspicuous and unobtrusive way. This environment requires information such as the person, his/her preferences, and habits which is available in the ubiquitous system. In this paper, we propose the context aware system that can provide the tailored information service for user in ubiquitous computing environment. Our system architecture is divided into 4 domain models such as context awareness, presentation, interface and inference domain. Each domain model can perform some predefined tasks independently. And we suggest the hybrid algorithm combined with fuzzy and Bayesian method in order to reason what is the suitable information for user. We show the possibility for the real application through applying the system to the TGA (Tour Guide Assistant) for Kyoungju historical site.-
dc.publisher한국CDE학회-
dc.title유비쿼터스 환경에서 상황인지 기반 문화재 답사도우미 시스템-
dc.typeArticle-
dc.description.journalClass2-
dc.identifier.bibliographicCitation한국CDE학회 논문집, v.11, no.5, pp.365 - 374-
dc.citation.title한국CDE학회 논문집-
dc.citation.volume11-
dc.citation.number5-
dc.citation.startPage365-
dc.citation.endPage374-
dc.description.journalRegisteredClasskci-
dc.identifier.kciidART001099443-
dc.subject.keywordAuthorUbiquitous Environment-
dc.subject.keywordAuthorWeb Service-
dc.subject.keywordAuthorAgent-
dc.subject.keywordAuthorContext-
dc.subject.keywordAuthorFuzzy logic-
dc.subject.keywordAuthorBayesian Network-
dc.subject.keywordAuthorUbiquitous Environment-
dc.subject.keywordAuthorWeb Service-
dc.subject.keywordAuthorAgent-
dc.subject.keywordAuthorContext-
dc.subject.keywordAuthorFuzzy logic-
dc.subject.keywordAuthorBayesian Network-
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KIST Article > 2006
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