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2014 | OriginalPaper | Buchkapitel

Fuzzy and Cross-Lingual Ontology Matching Mediated by Background Knowledge

verfasst von : Konstantin Todorov, Celiné Hudelot, Peter Geibel

Erschienen in: Uncertainty Reasoning for the Semantic Web III

Verlag: Springer International Publishing

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Abstract

The paper proposes an ontology alignment framework with two core features: the use of background knowledge and the ability to handle imprecision in the matching process and the resulting concept alignments. The procedure is based on the use of a generic reference vocabulary, which is used to define an explicit semantic space for the ontologies to be matched. General-purpose background knowledge sources based on Wikipedia, such as Yago, appear to be appropriate choices of reference vocabularies. The outcome of the procedure is a combined fuzzy knowledge body which captures what is common in two source ontologies. The proposed approach allows to discover cross-concept relations of the kind many-to-many. An important application of the method is found in the field of cross-lingual ontology matching.

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Vorheriges Kapitel Finite Lattices Do Not Make Reasoning in Harder

Nächstes Kapitel Semantic Knowledge Discovery and Data-Driven Logical Reasoning from Heterogeneous Data Sources

http://oaei.ontologymatching.org

http://www-nlpir.nist.gov/projects/tv2005/

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Titel: Fuzzy and Cross-Lingual Ontology Matching Mediated by Background Knowledge
verfasst von: Konstantin Todorov
Celiné Hudelot
Peter Geibel
Verlag: Springer International Publishing
Buch: Uncertainty Reasoning for the Semantic Web III
Print ISBN: 978-3-319-13412-3

Electronic ISBN: 978-3-319-13413-0

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-319-13413-0_8

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