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dc.contributor.author허선-
dc.date.accessioned2019-04-23T07:16:30Z-
dc.date.available2019-04-23T07:16:30Z-
dc.date.issued2016-08-
dc.identifier.citation대한산업공학회지, v. 42, No. 4, Page. 249-256en_US
dc.identifier.issn1225-0988-
dc.identifier.urihttp://www.dbpia.co.kr/Journal/ArticleDetail/NODE06748683-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/102617-
dc.description.abstractRecently, transaction data is accumulated everywhere very rapidly. Association analysis methods are usually applied to analyze transaction data, but the methods have several problems. For example, these methods can only consider one-way relations among items and cannot reflect domain knowledge into analysis process. In order to overcome defect of association analysis methods, we suggest a transaction data analysis method based on probabilistic graphical model (PGM) in this study. The method we suggest has several advantages as compared with association analysis methods. For example, this method has a high flexibility, and can give a solution to various probability problems regarding the transaction data with relationships among items.en_US
dc.language.isoko_KRen_US
dc.publisher대한산업공학회en_US
dc.subjectProbabilistic Graphical Modelen_US
dc.subjectTransaction Dataen_US
dc.subjectAssociation Ruleen_US
dc.subjectPoint-Wise Mutual Informationen_US
dc.title트랜잭션 데이터 분석을 위한 확률 그래프 모형en_US
dc.title.alternativeProbabilistic Graphical Model for Transaction Data Analysisen_US
dc.typeArticleen_US
dc.relation.no4-
dc.relation.volume42-
dc.relation.page249-255-
dc.relation.journal대한산업공학회지-
dc.contributor.googleauthor안길승-
dc.contributor.googleauthor허선-
dc.relation.code2016018733-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING-
dc.identifier.pidhursun-
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COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > INDUSTRIAL AND MANAGEMENT ENGINEERING(산업경영공학과) > Articles
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