One way to increase the power of Qualitative Spatial Reasoning is to introduce proximity operators (such as close and far) that are surrogates for distance measures. These operators appear to be semi-quantitative in nature as opposed to purely qualitative. In the light of observations drawn from psychometric testing of perceived proximity, this paper discusses how a model to support proximal reasoning could be constructed. The relationships between the model and the raw data are described. Fuzzy set membership is used to reason about the degree of closeness. The formulation of queries involving proximity is presented, with the meaning of linguistic variables being instantiated within a given context at execution time.
CITATION STYLE
Gahegan, M. (1995). Proximity operators for qualitative spatial reasoning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 988, pp. 31–44). Springer Verlag. https://doi.org/10.1007/3-540-60392-1_3
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