Towards a general theory of action and time
Artificial Intelligence
Representation and processing of spatial expressions
Time Granularities in Databases, Data Mining and Temporal Reasoning
Time Granularities in Databases, Data Mining and Temporal Reasoning
A Geographer Looks at Spatial Information Theory
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Aggregations and constituents: geometric specification of multi-granular objects
Journal of Visual Languages and Computing
A theory of granular parthood based on qualitative cardinality and size measures
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
A size-based qualitative approach to the representation of spatial granularity
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Similarity measurement in context
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
User profiling with hierarchical context: an e-Retailer case study
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
Delayed synapses: an LSM model for studying aspects of temporal context in memory
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
Distributed spatial reasoning for wireless sensor networks
CONTEXT'11 Proceedings of the 7th international and interdisciplinary conference on Modeling and using context
UCS'06 Proceedings of the Third international conference on Ubiquitous Computing Systems
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Spatial and temporal granularity can be understood as parameters of context restricting the set of accessible objects in a context. Starting from the idea that this selection process depends to a large extent on the relation between the grain-size of the context and the local extension of the objects, the granularity of a context is in this article formalised as a class of possible sizes in the context. This formalisation is shown to be in accordance to well-known mathematical foundations on perceptual classification. An example for the case of temporal granularity illustrates how the introduction of new elements into a context may result in a more or less smooth shifting of the granularity leading to a classification of four different types of change of granularity. The results can be applied in a wide range of fields, e.g. in research on contextual reasoning and natural language understanding.