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Granularity as a Parameter of Context

  • Hedda R. Schmidtke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3554)

Abstract

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.

Keywords

Temporal Context Time Granularity Vague Predi Contextual Reasoning Partitioning Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hedda R. Schmidtke
    • 1
  1. 1.Department for InformaticsUniversity of HamburgHamburgGermany

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