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Cluster Computing
Erschienen in: Cluster Computing 4/2016

01.12.2016

Ontology algorithm using singular value decomposition and applied in multidisciplinary

verfasst von: Wei Gao, Yun Guo, Kaiyun Wang

Erschienen in: Cluster Computing | Ausgabe 4/2016

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Abstract

As a popular data management and computation tool, ontology is widely used in material science, biological genetics, chemistry, biology and pharmaceuticals. It can be regarded as a dictionary or a database, and the key of various ontology applications is similarity measuring between concepts in ontology. In this paper, we propose a new ontology learning algorithm for ontology similarity measuring and ontology mapping by means of singular value decomposition method and deterministic sampling iteration. Then, the new ontology learning is applied in plant science, gene biology, bionics and physics ontologies. The data results show the high efficiency of our singular value decomposition based ontology learning algorithm for ontology similarity measuring and ontology mapping.
Vorheriger Artikel Safety verification of finite real-time nonlinear hybrid systems using enhanced group preserving scheme
Nächster Artikel Research trends in sustainable operation: a bibliographic coupling clustering analysis from 1988 to 2016

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Metadaten
Titel
Ontology algorithm using singular value decomposition and applied in multidisciplinary
verfasst von
Wei Gao
Yun Guo
Kaiyun Wang
Publikationsdatum
01.12.2016
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 4/2016
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-016-0651-0

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