淡江大學機構典藏:Item 987654321/91962
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/91962


    Title: A Semantic Web Approach to Heterogeneous Metadata Integration
    Authors: Liao, Shu-hsien
    Contributors: 淡江大學管理科學學系
    Keywords: Face recognition;principle component analysis;PCA;two dimensional principle component analysis;2DPCA;discrete cosine transformation;DCT;weighted voting;spatial domain;frequency domain;genetic algorithms
    Date: 2010-02
    Issue Date: 2013-08-12 11:25:04 (UTC+8)
    Publisher: Springer-Verlag Berlin, Heidelberg
    Abstract: 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.
    Relation: Lecture Notes in Artificial Intelligence 6421,　p.205-214
    DOI: 10.1007/978-3-642-16693-8_23
    Appears in Collections:[Department of Management Sciences] Journal Article

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