A Semantic Web Approach to Heterogeneous Metadata Integration

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題名:	A Semantic Web Approach to Heterogeneous Metadata Integration
作者:	Liao, Shu-hsien
貢獻者:	淡江大學管理科學學系
關鍵詞:	Face recognition;principle component analysis;PCA;two dimensional principle component analysis;2DPCA;discrete cosine transformation;DCT;weighted voting;spatial domain;frequency domain;genetic algorithms
日期:	2010-02
上傳時間:	2013-08-12 11:25:04 (UTC+8)
出版者:	Springer-Verlag Berlin, Heidelberg
摘要:	Heterogeneous metadata integration is an issue in digital libraries. Mapping is often used for an integrated metadata access, but the implicit knowledge and relations embedded in metadata are ignored. This paper aims to present a semantic web approach to heterogeneous metadata integration of biodiversity repositories. First, implicit knowledge and relations in metadata are extracted out and transformed into a shared ontology with expression of RDF and OWL languages. Next the shared ontology plays an inter-lingua role in harmonizing heterogeneous metadata to achieve an ontology mapping with a unified view. Then the shared ontology is expressed by SWRL for inference query to offer in-depth semantic discovery. Finally four question answering oriented queries are employed to examine the feasibility of the shared ontology for heterogeneous metadata integration.
關聯:	Lecture Notes in Artificial Intelligence 6421,　p.205-214
DOI:	10.1007/978-3-642-16693-8_23
顯示於類別:	[管理科學學系暨研究所] 期刊論文

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