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Association Rule Mining and Network Analysis in Oriental Medicine

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dc.contributor.authorYang, Dong Hoon-
dc.contributor.authorKang, Ji Hoon-
dc.contributor.authorPark, Young Bae-
dc.contributor.authorPark, Young Jae-
dc.contributor.authorOh, Hwan Sup-
dc.contributor.authorKim, Seoung Bum-
dc.date.accessioned2021-09-06T03:28:09Z-
dc.date.available2021-09-06T03:28:09Z-
dc.date.created2021-06-14-
dc.date.issued2013-03-15-
dc.identifier.issn1932-6203-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/103736-
dc.description.abstractExtracting useful and meaningful patterns from large volumes of text data is of growing importance. In the present study we analyze vast amounts of prescription data, generated from the book of oriental medicine to identify the relationships between the symptoms and the associated medicines used to treat these symptoms. The oriental medicine book used in this study (called Bangyakhappyeon) contains a large number of prescriptions to treat about 54 categorized symptoms and lists the corresponding herbal materials. We used an association rule algorithm combined with network analysis and found useful and informative relationships between the symptoms and medicines.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherPUBLIC LIBRARY SCIENCE-
dc.subjectTRADITIONAL CHINESE MEDICINE-
dc.subjectKNOWLEDGE DISCOVERY-
dc.titleAssociation Rule Mining and Network Analysis in Oriental Medicine-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Seoung Bum-
dc.identifier.doi10.1371/journal.pone.0059241-
dc.identifier.scopusid2-s2.0-84875032769-
dc.identifier.wosid000316409800074-
dc.identifier.bibliographicCitationPLOS ONE, v.8, no.3-
dc.relation.isPartOfPLOS ONE-
dc.citation.titlePLOS ONE-
dc.citation.volume8-
dc.citation.number3-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.subject.keywordPlusTRADITIONAL CHINESE MEDICINE-
dc.subject.keywordPlusKNOWLEDGE DISCOVERY-
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