Abstract
Reasoning about spatial relevance is important for intelligent spatial information retrieval. In heterogeneous and distributed systems like the Semantic Web, spatial reasoning has to be based on light-weight, interoperable and easy-to-use spatial metadata.
In this paper we present an approach to an intuitive and user-friendly creation and application of spatial metadata that are used for spatial relevance reasoning. The metadata are based on discrete approximations of place name regions. Based on knowledge about cognitive aspects of preferred spatial models, our approach allows for the representation and intuitive modelling of indeterminate regions in addition to regions with well-known boundaries.
Keywords
- Geographic Information System
- Discrete Approximation
- Decomposition Tree
- Spatial Reasoning
- Intuitive Modelling
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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Vögele, T., Schlieder, C., Visser, U. (2003). Intuitive Modelling of Place Name Regions for Spatial Information Retrieval. In: Kuhn, W., Worboys, M.F., Timpf, S. (eds) Spatial Information Theory. Foundations of Geographic Information Science. COSIT 2003. Lecture Notes in Computer Science, vol 2825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39923-0_16
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DOI: https://doi.org/10.1007/978-3-540-39923-0_16
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