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Semantic Metadata Enrichment


Abstract

The amount of digitised content and appendant metadata records managed by today’s digital library systems is growing rapidly and the community has already started to think about advanced search mechanisms that guide end users through the information flood. Ontologies and semantic search mechanisms will play a key role in solving that issue, presumed that stored metadata records are ontology aware and machine processable also on a semantic level. However, this is not the case when existing legacy metadata is integrated into such systems. In this project we develop a semi-automatic approach for semantically enriching large sets of legacy metadata, which exploits the power of machine learning techniques. Following our approach expert users that manage today’s digital libraries can easily migrate existing metadata into modern digital library systems which consider machine processable semantics.

Further details
Type
internal research projects
Executive
Faculty of Computer Science
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Faculty of Computer Science
University of Vienna

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