We propose Contextualized Knowledge Repository (CKR): an adaptation of one of the well studied logics of context in AI for the Semantic Web. A CKR is composed of a set of DL knowledge bases, which are embedded in a context by a set of qualifying attributes (time, space, topic, etc.) specifying the boundaries within which the knowledge base is assumed to be true. Contexts of a CKR are organized by a hierarchical coverage relation, which enables an effective representation of knowledge and a flexible method for its reuse between the contexts. The paper defines syntax and semantics for CKR; shows that concept satisfiability and subsumption are decidable with the complexity upper bound of 2NExpTime, and finally it provides a sound and complete Natural Deduction calculus for CKR.

Contextualized Knowledge Repositories for the Semantic Web

Serafini, Luciano;Homola, Martin
2011

Abstract

We propose Contextualized Knowledge Repository (CKR): an adaptation of one of the well studied logics of context in AI for the Semantic Web. A CKR is composed of a set of DL knowledge bases, which are embedded in a context by a set of qualifying attributes (time, space, topic, etc.) specifying the boundaries within which the knowledge base is assumed to be true. Contexts of a CKR are organized by a hierarchical coverage relation, which enables an effective representation of knowledge and a flexible method for its reuse between the contexts. The paper defines syntax and semantics for CKR; shows that concept satisfiability and subsumption are decidable with the complexity upper bound of 2NExpTime, and finally it provides a sound and complete Natural Deduction calculus for CKR.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/31940
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