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WB-T: A WORDNET-BASED TRANSLATION ALGORITHM FOR RDB-TO-XML CONVERSION

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dc.contributor.authorKim, Jangwon-
dc.contributor.authorJeong, Dongwon-
dc.contributor.authorKim, Jinhyung-
dc.contributor.authorBaik, Doo-Kwon-
dc.date.accessioned2021-09-08T20:11:28Z-
dc.date.available2021-09-08T20:11:28Z-
dc.date.created2021-06-19-
dc.date.issued2009-02-
dc.identifier.issn0218-0014-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/120654-
dc.description.abstractXML has grown to represent and exchange information which is used widely in various computing areas such as web environment, mobile environment, data management systems. Especially, the most important issue for practical purposes is how to achieve the interoperability between XML model and relational database model. Until now, various algorithms have been proposed to achieve it. However, existing algorithms do not consider implicit referential integrity relation. VP-T and QP-T have been proposed to resolve the problem - QP-T enhanced VP-T based on query pattern. However, both have a critical restriction that column titles for an attribute are identically represented. Therefore, several referential integrity relations might not be extracted. In this paper, we introduce a novel translation algorithm whose name is WordNet-based Translation algorithm (WB-T) to resolve the above issues. WB-T can check similarity between column titles based on WordNet and extract more exact implicit referential integrity relation than the previous algorithms. WB-T provides improved extraction accuracy and reduces the extraction time.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD-
dc.subjectENTITY-RELATIONSHIP SCHEMA-
dc.subjectRELATIONAL DATABASE-
dc.titleWB-T: A WORDNET-BASED TRANSLATION ALGORITHM FOR RDB-TO-XML CONVERSION-
dc.typeArticle-
dc.contributor.affiliatedAuthorBaik, Doo-Kwon-
dc.identifier.doi10.1142/S0218001409007053-
dc.identifier.scopusid2-s2.0-65249130596-
dc.identifier.wosid000264491300012-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, v.23, no.1, pp.145 - 158-
dc.relation.isPartOfINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE-
dc.citation.titleINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE-
dc.citation.volume23-
dc.citation.number1-
dc.citation.startPage145-
dc.citation.endPage158-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusENTITY-RELATIONSHIP SCHEMA-
dc.subject.keywordPlusRELATIONAL DATABASE-
dc.subject.keywordAuthorRelational database schema-
dc.subject.keywordAuthorXML schema-
dc.subject.keywordAuthorreferential integrity-
dc.subject.keywordAuthorimplicit referential integrity-
dc.subject.keywordAuthorWordNet-
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