Semantic Web languages cannot currently represent vague or uncertain information. However, their crisp model-theoretic semantics can be extended to represent uncertainty in much the same way first-order logic was extended to fuzzy logic. We show how the interpretation of an RDF graph (or an RDF Schema ontology) can be a matter of values, addressing a common problem in real-life knowledge management. While unmodified RDF triples can be interpreted according to the new semantics, an extended syntax is needed in order to store fuzzy membership values within the statements. We give conditions an extended interpretation must meet to be a model of an extended graph. Reasoning in the resulting fuzzy languages can be implemented by current inferencers with minimal adaptations

A Fuzzy Semantics for the Resource Description FrameworkUncertainty Reasoning for the Semantic Web / Mazzieri, Mauro; Dragoni, Aldo Franco. - STAMPA. - 5327:(2008), pp. 244-261. (Intervento presentato al convegno ISWC International Workshops on Uncertainty Reasoning for the Semantic Web, URSW 2005-2007 tenutosi a Galway Ireland) [10.1007/978-3-540-89765-1_15].

A Fuzzy Semantics for the Resource Description FrameworkUncertainty Reasoning for the Semantic Web

MAZZIERI, MAURO;DRAGONI, Aldo Franco
2008-01-01

Abstract

Semantic Web languages cannot currently represent vague or uncertain information. However, their crisp model-theoretic semantics can be extended to represent uncertainty in much the same way first-order logic was extended to fuzzy logic. We show how the interpretation of an RDF graph (or an RDF Schema ontology) can be a matter of values, addressing a common problem in real-life knowledge management. While unmodified RDF triples can be interpreted according to the new semantics, an extended syntax is needed in order to store fuzzy membership values within the statements. We give conditions an extended interpretation must meet to be a model of an extended graph. Reasoning in the resulting fuzzy languages can be implemented by current inferencers with minimal adaptations
2008
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783540897644
9783540897651
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/137063
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