A Parameterized Representation of Uncertain Conceptual Spaces

Abstract

AbstractMost conceptual modeling in geographic information science to date has used a symbolic approach with little or no recognition of the semantic uncertainty often found in geographic concepts. This work describes a concept model based on parameterized concept descriptions that uses a spatial metaphor, the conceptual space, as an organizing structure (Gärdenfors 2000). This cognitive theory of conceptual spaces is combined with a formal representation of semantic uncertainty based on rough fuzzy sets. The conceptual space then represents each concept as a collection of rough fuzzy property definitions with associated salience weights, where a property itself can be treated as a special case of a concept. Instead of explicitly defining concept hierarchies, we can allow different conceptual structures to emerge through measures of concept inclusion and similarity. A land use/land cover example demonstrates how the model represents concepts, concept similarity, hierarchical structures and the context dependence of concepts. The final section of the paper points to the need for further studies of context effects, concept similarity measures, and uncertainty representation using the proposed model.