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dc.contributor.author차재혁-
dc.date.accessioned2016-07-28T01:07:31Z-
dc.date.available2016-07-28T01:07:31Z-
dc.date.issued2015-02-
dc.identifier.citationInformation, v. 18, no.2, Page. 753-762en_US
dc.identifier.issn1343-4500-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/22299-
dc.identifier.urihttp://search.proquest.com/openview/3bfd52aa35137b9e58fae300abe089f5/1?pq-origsite=gscholar&cbl=936334-
dc.description.abstractOntology is one important method by which data is expressed in Semantic Web. For Semantic Web based on ontology, it is important to produce ontology of various domains, but for sharing and expanding ontology, ontology matching work is very important. Using only possessed information of concept in ontology matching has limitation. Therefore, in recent studies, using relationship between concepts, that is, structural information, precision can be being raised. For this, if we use structurebased ontology matching method, its precision can be increased much, but because its complexity metric is quite high, it is difficult to implement this method in large sized ontology. In this study, to decrease complexity metric, a technique with which structural information is changed into sequential information and a DTW algorithm application on ontology matching have been suggested. Also, it has been proved through testing that by implementing the method which has been suggested in this study, the performance of existing multi strategic systems can be improved.-
dc.publisherInternational Information Instituteen_US
dc.titleOntology Matching Performance Improvement using DTWen_US
dc.typeArticleen_US
dc.relation.page753-762-
dc.relation.journalInformation-
dc.contributor.googleauthorChang, Byoungchol-
dc.contributor.googleauthorLee, Jin-
dc.contributor.googleauthorCha, Jaehyuk-
dc.relation.code2015026103-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF COMPUTER SCIENCE-
dc.identifier.pidchajh-
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COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE AND ENGINEERING(컴퓨터공학부) > Articles
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