Qualitative Geometry for Shape Recognition
Applied Intelligence
Attaching Context-Aware Services to Moving Locations
IEEE Internet Computing
A Survey of Context-Aware Mobile Computing Research
A Survey of Context-Aware Mobile Computing Research
Context-Aware Computing Applications
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
Toward a geometry of common sense: a semantics and a complete axiomatization of mereotopology
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Aggregations and constituents: geometric specification of multi-granular objects
Journal of Visual Languages and Computing
UCS'06 Proceedings of the Third international conference on Ubiquitous Computing Systems
Granularity as a parameter of context
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Towards Ontology-Based Formal Verification Methods for Context Aware Systems
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Positions, regions, and clusters: strata of granularity in location modelling
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Distributed spatial reasoning for wireless sensor networks
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
Applied Ontology
Applied Ontology
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A local spatial context is an area currently under consideration in a spatial reasoning process. The boundary between this area and the surrounding space together with the spatial granularity of the representation separates what is spatially relevant from what is irrelevant at a given time. The approach discussed in this article differs from other approaches to spatial granularity as it focusses not on a partitioning of the spatial domain, but on the notions of grain-size and the limited extent of a spatial context as primary factors of spatial granularity. Starting from a mereotopological characterization of these concepts, the notions of relevant and irrelevant extension in a context are defined. The approach is qualitative in the sense that quantitative, metric concepts are not required. The axiomatic characterization is thoroughly evaluated: it is compared to other mereotopological characterizations of spatial granularity; soundness is proven with an example model; and applicability for Knowledge Representation is illustrated with definitions for common sense conceptualizations of sameness, and adjacency of locations.