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EUREEKA: Deepening the Semantic Web by More Efficient Emergent Knowledge Representation and Processing

ARAN - Access to Research at NUI Galway

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dc.contributor.author Novacek, Vit en
dc.date.accessioned 2010-01-22T10:10:47Z en
dc.date.available 2010-01-22T10:10:47Z en
dc.date.issued 2008 en
dc.identifier.citation Vit Novacek "Christian Bizer, Anupam Joshi (editors) "EUREEKA: Deepening the Semantic Web by More Efficient Emergent Knowledge Representation and Processing", Proceedings of the Poster and Demonstration Session at the 7th International Semantic Web Conference (ISWC2008), in conjunction with International Semantic Web Conference 2008, CEUR-WS, 2008. en
dc.identifier.uri http://hdl.handle.net/10379/626 en
dc.description.abstract One of the major Semantic Web challenges is the knowledge acquisition bottleneck. New content on the web is produced much faster than the respective machine readable annotations, while a scalable knowledge extraction from the legacy resources is still largely an open problem. This poster presents an ongoing research on an empirical knowledge representation and reasoning framework, which is tailored to robust and meaningful processing of emergent, automatically learned ontologies. According to the preliminary results of our EUREEKA1 prototype, the proposed framework can substantially improve the applicability of the rather messy emergent knowledge and thus facilitate the knowledge acquisition in an unprecedented way. en
dc.format application/pdf en
dc.language.iso en en
dc.publisher CEUR-WS en
dc.subject.lcsh Knowledge management en
dc.subject.lcsh Semantic web en
dc.title EUREEKA: Deepening the Semantic Web by More Efficient Emergent Knowledge Representation and Processing en
dc.type Workshop paper en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder NEPOMUK en

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