Abstract:
In one embodiment, prior to similarity measure computation, concept expansion is applied to an original ontology to generate an expanded ontology having the original concepts plus one or more pseudo-concepts, wherein at least one original concept is defined using a hierarchy of (possibly transitive) properties. As a result, the similarity measure computation can produce results that are better than those produced using conventional techniques. In one implementation, the similarity measure computation involves combining two similarity results: a first similarity result corresponding to common semantics found in the two concepts and a second similarity result corresponding to dissimilar semantics found in the two concepts.
Abstract:
In one embodiment, prior to similarity measure computation, concept expansion is applied to an original ontology to generate an expanded ontology having the original concepts plus one or more pseudo-concepts, wherein at least one original concept is defined using a hierarchy of (possibly transitive) properties. As a result, the similarity measure computation can produce results that are better than those produced using conventional techniques. In one implementation, the similarity measure computation involves combining two similarity results: a first similarity result corresponding to common semantics found in the two concepts and a second similarity result corresponding to dissimilar semantics found in the two concepts.
Abstract:
In one embodiment, prior to similarity measure computation, concept expansion based on disjunctive normal form (DNF) decomposition and non-conventional reasoning is applied to an original ontology to generate an expanded ontology having the original concepts plus one or more pseudo concepts. As a result, the similarity measure computation can produce results that more accurately reflect a human point of view than convention techniques.
Abstract:
In one embodiment, prior to similarity measure computation, concept expansion based on disjunctive normal form (DNF) decomposition and non-conventional reasoning is applied to an original ontology to generate an expanded ontology having the original concepts plus one or more pseudo concepts. As a result, the similarity measure computation can produce results that more accurately reflect a human point of view than convention techniques.
Abstract:
A capability for managing a representation of a smart environment is presented herein. The capability for managing a representation of a smart environment is configured to support augmented reality (AR)-based management of a representation of a smart environment, which may include AR-based generation of a representation of the smart environment, AR-based alignment of the representation of the smart environment with the physical reality of the smart environment, and the like.
Abstract:
A capability for managing a representation of a smart environment is presented herein. The capability for managing a representation of a smart environment is configured to support augmented reality (AR)-based management of a representation of a smart environment, which may include AR-based generation of a representation of the smart environment, AR-based alignment of the representation of the smart environment with the physical reality of the smart environment, and the like.