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
2011-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
