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dc.contributor.authorKuo, TTen_US
dc.contributor.authorTseng, SSen_US
dc.contributor.authorLin, YTen_US
dc.date.accessioned2014-12-08T15:41:30Z-
dc.date.available2014-12-08T15:41:30Z-
dc.date.issued2003en_US
dc.identifier.isbn3-540-40455-4en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/28219-
dc.description.abstractFor a variety of knowledge sources and time-critical tasks, knowledge fusion seems to be a proper concern. In this paper, we proposed a reconstruction concept and a three-phase knowledge fusion framework which utilizes the shared vocabulary ontology and addresses the problem of meta-knowledge construction. In the framework, we also proposed relationship graph, an intermediate knowledge representation, and two criteria for the fusion process. An evaluation of the implementation of our proposed knowledge fusion framework in the intrusion detection systems domain is also given.en_US
dc.language.isoen_USen_US
dc.titleOntology-based knowledge fusion framework using graph partitioningen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.journalDEVELOPMENTS IN APPLIED ARTIFICIAL INTELLIGENCEen_US
dc.citation.volume2718en_US
dc.citation.spage11en_US
dc.citation.epage20en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000184852400002-
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