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dc.contributor.authorBock, Jürgen*
dc.date.accessioned2021-02-11T21:41:34Z
dc.date.available2021-02-11T21:41:34Z
dc.date.issued2013*
dc.date.submitted2019-07-30 20:02:02*
dc.identifier35487*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/55253
dc.description.abstractIt is investigated how biologically-inspired optimisation methods can be used to compute alignments between ontologies. Independent of particular similarity metrics, the developed techniques demonstrate anytime behaviour and high scalability. Due to the inherent parallelisability of these population-based algorithms it is possible to exploit dynamically scalable cloud infrastructures - a step towards the provisioning of Alignment-as-a-Service solutions for future semantic applications.*
dc.languageEnglish*
dc.subjectHF5001-6182*
dc.subject.othercloud*
dc.subject.otherevolution*
dc.subject.otheralignment*
dc.subject.otherPSO*
dc.subject.otherontology*
dc.titleOntology Alignment using Biologically-inspired Optimisation Algorithms*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000030761*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
virtual.oapen_relation_isPublishedBy.publisher_nameKIT Scientific Publishing
virtual.oapen_relation_isPublishedBy.publisher_websitehttp://www.ksp.kit.edu/
oapen.relation.isbn9783866449367*
oapen.pagesXIV, 220 p.*


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