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dc.citation.endPage 15 -
dc.citation.number 2 -
dc.citation.startPage 1 -
dc.citation.title ADVANCES IN INTELLIGENT AND SOFT COMPUTING -
dc.citation.volume 82 -
dc.contributor.author Bien, Zeungnam -
dc.contributor.author Lee, Sangwan -
dc.date.accessioned 2023-12-22T07:36:17Z -
dc.date.available 2023-12-22T07:36:17Z -
dc.date.created 2013-05-24 -
dc.date.issued 2010-01 -
dc.description.abstract A growing proportion of the aged in population provokes shortage of caregivers and restructuring of living spaces. One of the most promising solutions is to provide with a smart home environment that ensures independence of users. In this paper, we first call attention to the fact that a learning capability of human behavior patterns can play a central role in adequate functioning of such systems. Specifically, we give an overview of important related studies to illustrate how a variety of learning functions can be successfully incorporated into the smart home environment. We then present our approaches towards the issues of life-long learning and non-supervised learning, which are considered essential aspects of a smart home system. The two learning schemes are shown to be satisfactory in facilitating independent living over different time scales and with less human intervention. Finally, we mention about a prospective model of a future smart home -
dc.identifier.bibliographicCitation ADVANCES IN INTELLIGENT AND SOFT COMPUTING, v.82, no.2, pp.1 - 15 -
dc.identifier.doi 10.1007/978-3-642-15660-1_1 -
dc.identifier.issn 1867-5662 -
dc.identifier.scopusid 2-s2.0-80052958820 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/2952 -
dc.identifier.url https://link.springer.com/chapter/10.1007%2F978-3-642-15660-1_1 -
dc.language 영어 -
dc.publisher SPRINGER VERLAG -
dc.title Foreword: Learning Structure of Human Behavior Patterns in a Smart Home System -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.description.journalRegisteredClass scopus -

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