2010
DOI: 10.1080/08839510903448650
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Augmenting Subsumption Propagation in Distributed Description Logics

Abstract: Distributed description logics (DDL) enable reasoning with multiple ontologies interconnected by directional semantic mapping, called bridge rules. Bridge rules map concepts of a source ontology into concepts of a target ontology. Concept subsumptions of the source ontology can be propagated according to a propagation pattern expressed by means of bridge rules into concept subsumptions of the target ontology. In the basic formulation of DDL, such a propagation is mostly limited to cases when pairs of ontologie… Show more

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Cited by 12 publications
(9 citation statements)
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“…We prove the main theorem by induction on φ. Step The DFOL encoding of QML shown above decouples the semantics of the modal operator , captured by bridge rules (38) and (39), and the assumptions on the possible worlds domains, captured by the bridge rule (40). Different assumptions on the possible worlds domains can be encoded by means of different bridge rules on the equality predicate, thus retaining the bridge rules for unchanged.…”
Section: Kripke Semantics For Qmlmentioning
confidence: 99%
See 1 more Smart Citation
“…We prove the main theorem by induction on φ. Step The DFOL encoding of QML shown above decouples the semantics of the modal operator , captured by bridge rules (38) and (39), and the assumptions on the possible worlds domains, captured by the bridge rule (40). Different assumptions on the possible worlds domains can be encoded by means of different bridge rules on the equality predicate, thus retaining the bridge rules for unchanged.…”
Section: Kripke Semantics For Qmlmentioning
confidence: 99%
“…In [40] additional constraints on the domain relation are added in order to augment the information flow between different ontologies induced by DDL ontology mappings. Of particular interest are the bridge rules that support the transitive propagation of mappings:…”
Section: Distributed Description Logicsmentioning
confidence: 99%
“…Due to their capacity to combine logical reasoning over multiple knowledge sources, MCS have been used to formalize distributed FOL (Ghidini & Serafini, 1998), and later Distributed Description Logic (DDL) (Borgida & Serafini, 2003). The latter approach, in particular, proved to be influential and sparked considerable interest in distributed ontologies, where the power of MCS is used either to make alignments between heterogeneous and possibly ambiguous ontologies that are to be combined in reasoning (Ghidini & Serafini, 2008; Ghidini et al ., 2008), or to facilitate truly distributed inference (Serafini & Tamilin, 2004; Serafini et al ., 2005; Homola & Serafini, 2010). Both directions may be useful in AmI systems, in cases when more than one ontology is employed within a system, possibly governed by independent agents.…”
Section: Conflict Resolution Approachesmentioning
confidence: 99%
“…Luciano Serafini, one of the initiators of the DDL formalism, has proposed a formalism and a tableau algorithm for dealing with mappings and axioms involving nominals in DDLs (Serafini, 2007;Homola & Serafini, 2010;Serafini & Homola, 2012). Luciano Serafini, one of the initiators of the DDL formalism, has proposed a formalism and a tableau algorithm for dealing with mappings and axioms involving nominals in DDLs (Serafini, 2007;Homola & Serafini, 2010;Serafini & Homola, 2012).…”
Section: Note On the Distributed Description Logic Implementation Of mentioning
confidence: 99%
“…In particular, the DDL formalism did not allow the use of nominals in bridge rules and this is still the case in the current version of the D rago system. Luciano Serafini, one of the initiators of the DDL formalism, has proposed a formalism and a tableau algorithm for dealing with mappings and axioms involving nominals in DDLs (Serafini, 2007; Homola & Serafini, 2010; Serafini & Homola, 2012). Thus, the use of nominals in axioms hereafter is justified.…”
Section: Using Distributed Description Logics For Reasoning With Multmentioning
confidence: 99%