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텍스트마이닝을 활용한 건설분야 트랜드 분석

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dc.contributor.author정철우-
dc.contributor.author김재준-
dc.date.accessioned2022-07-16T14:50:32Z-
dc.date.available2022-07-16T14:50:32Z-
dc.date.created2021-05-13-
dc.date.issued2012-06-
dc.identifier.issn1738-0790-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/165306-
dc.description.abstractIn this paper, we present new methods for identifying keywords for foresight topics that utilize the internet and textmining techniques to draw objective and quantified information that support experts’ qualitative opinions and evaluations in foresight. Furthermore, by applying this fabricated procedure, we have derived keywords to analyze priorities in architectural engineering. Not much difference between qualitative methods of experts and quantitative methods such as text mining has been observed from comparison between technologies derived via qualitative method from “The Science Technology Vision” (control group). Therefore, as a quantitative tool useful for drawing keywords for foresight, textmining can supplement quantitative analysis by experts. In addition, depending on the level and type of raw data, text mining can bring better results in deriving foresight keywords. For this reason, research activities accommodating Internet search results and the development of textmining methods for analyzing current trends are in demand.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국디지털건축·인테리어학회-
dc.title텍스트마이닝을 활용한 건설분야 트랜드 분석-
dc.title.alternativeAnalysis of trend in construction using textmining method-
dc.typeArticle-
dc.contributor.affiliatedAuthor김재준-
dc.identifier.bibliographicCitation한국디지털건축인테리어학회 논문집, v.12, no.2, pp.53 - 60-
dc.relation.isPartOf한국디지털건축인테리어학회 논문집-
dc.citation.title한국디지털건축인테리어학회 논문집-
dc.citation.volume12-
dc.citation.number2-
dc.citation.startPage53-
dc.citation.endPage60-
dc.type.rimsART-
dc.identifier.kciidART001670691-
dc.description.journalClass2-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.description.journalRegisteredClassother-
dc.subject.keywordAuthorTextminign-
dc.subject.keywordAuthorForesight-
dc.subject.keywordAuthorTrend-
dc.subject.keywordAuthorTF-DI-
dc.subject.keywordAuthor텍스트마이닝-
dc.subject.keywordAuthor미래예측-
dc.subject.keywordAuthor트랜드분석-
dc.identifier.urlhttps://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=JAKO201218449217073&SITE=CLICK-
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