Abstract
Over the past few years, several alternative approaches have been suggested to represent the spatial knowledge that emerges from natural environments. This paper introduces a rule-based approach whose objective is to generate a spatial semantic network derived from several humans reporting a navigation process in a natural environment. Verbal descriptions are decomposed and characterized by a graph-based model where actions and landmarks are the main abstractions. A set of rules implemented as first order predicate calculus are identified and applied, and allow to merge the common knowledge inferred from route descriptions. A spatial semantic network is derived and provides a global and semantic view of the environment. The whole approach is illustrated by a case study and some preliminary experimental results.
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Belouaer, L., Brosset, D., Claramunt, C. (2013). Modeling Spatial Knowledge from Verbal Descriptions. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds) Spatial Information Theory. COSIT 2013. Lecture Notes in Computer Science, vol 8116. Springer, Cham. https://doi.org/10.1007/978-3-319-01790-7_19
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DOI: https://doi.org/10.1007/978-3-319-01790-7_19
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