Decentralized case-based reasoning for the semantic web
Identifieur interne : 006373 ( Main/Exploration ); précédent : 006372; suivant : 006374Decentralized case-based reasoning for the semantic web
Auteurs : Mathieu D'Aquin [France] ; Jean Lieber [France] ; Amedeo Napoli [France]Source :
- Lecture notes in computer science [ 0302-9743 ] ; 2005.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
Decentralized case-based reasoning (DzCBR) is a reasoning framework that addresses the problem of adaptive reasoning in a multi-ontology environment. It is a case-based reasoning (CBR) approach which relies on contextualized ontologies in the C-OWL formalism for the representation of domain knowledge and adaptation knowledge. A context in C-OWL is used to represent a particular viewpoint, containing the knowledge needed to solve a particular local problem. Semantic relations between contexts and the associated reasoning mechanisms allow the CBR process in a particular viewpoint to reuse and share information about the problem and the already found solutions in the other viewpoints.
Affiliations:
Links toward previous steps (curation, corpus...)
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- to stream PascalFrancis, to step Curation: 000546
- to stream PascalFrancis, to step Checkpoint: 000505
- to stream Main, to step Merge: 006642
- to stream Main, to step Curation: 006373
Le document en format XML
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<term>Web sémantique</term>
<term>Ontologie</term>
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<term>Réutilisation</term>
<term>Raisonnement basé sur cas</term>
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<front><div type="abstract" xml:lang="en">Decentralized case-based reasoning (DzCBR) is a reasoning framework that addresses the problem of adaptive reasoning in a multi-ontology environment. It is a case-based reasoning (CBR) approach which relies on contextualized ontologies in the C-OWL formalism for the representation of domain knowledge and adaptation knowledge. A context in C-OWL is used to represent a particular viewpoint, containing the knowledge needed to solve a particular local problem. Semantic relations between contexts and the associated reasoning mechanisms allow the CBR process in a particular viewpoint to reuse and share information about the problem and the already found solutions in the other viewpoints.</div>
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