完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Kuo, TT | en_US |
dc.contributor.author | Tseng, SS | en_US |
dc.contributor.author | Lin, YT | en_US |
dc.date.accessioned | 2014-12-08T15:41:30Z | - |
dc.date.available | 2014-12-08T15:41:30Z | - |
dc.date.issued | 2003 | en_US |
dc.identifier.isbn | 3-540-40455-4 | en_US |
dc.identifier.issn | 0302-9743 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/28219 | - |
dc.description.abstract | For 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.iso | en_US | en_US |
dc.title | Ontology-based knowledge fusion framework using graph partitioning | en_US |
dc.type | Article; Proceedings Paper | en_US |
dc.identifier.journal | DEVELOPMENTS IN APPLIED ARTIFICIAL INTELLIGENCE | en_US |
dc.citation.volume | 2718 | en_US |
dc.citation.spage | 11 | en_US |
dc.citation.epage | 20 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000184852400002 | - |
顯示於類別: | 會議論文 |