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제품별 구매고객 예측을 위한 인공신경망, 귀납규칙 및 IRANN 모형

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dc.contributor.author정수미-
dc.contributor.author이건호-
dc.date.available2018-05-10T17:42:52Z-
dc.date.created2018-04-17-
dc.date.issued2005-12-
dc.identifier.issn1225-1119-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/19451-
dc.description.abstractIt is effective and desirable for a proper customer relationship management or marketing to focus on the specific customers rather than a number of non specific customers. This study forecasts the prospective purchasers with high probability to purchase a specific product. Artificial Neural Network(ANN) can classify the characteristics of the prospective purchasers but ANN has a limitation in comprehending of outputs. ANN is integrated into IRANN with IR of decision tree program C5.0 to comprehend and analyze the outputs of ANN. We compare and analyze the accuracy of ANN, IR, and IRANN each other.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국경영과학회-
dc.relation.isPartOf한국경영과학회지-
dc.subjectForecasting Purchasers-
dc.subjectCustomized Marketing-
dc.subjectInduction Rule-
dc.subjectNeural Network-
dc.title제품별 구매고객 예측을 위한 인공신경망, 귀납규칙 및 IRANN 모형-
dc.title.alternativeArtificial Neural Network, Induction Rules, and IRANN to Forecast Purchasers for a Specific Product-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.bibliographicCitation한국경영과학회지, v.30, no.4, pp.117 - 130-
dc.identifier.kciidART001094323-
dc.description.journalClass2-
dc.citation.endPage130-
dc.citation.number4-
dc.citation.startPage117-
dc.citation.title한국경영과학회지-
dc.citation.volume30-
dc.contributor.affiliatedAuthor이건호-
dc.identifier.urlhttps://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001094323-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorForecasting Purchasers-
dc.subject.keywordAuthorCustomized Marketing-
dc.subject.keywordAuthorInduction Rule-
dc.subject.keywordAuthorNeural Network-
dc.description.journalRegisteredClasskci-
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