The design and analysis of spatial data structures
The design and analysis of spatial data structures
Qualitative representation of positional information
Artificial Intelligence
Imprecise reasoning in geographic information systems
Fuzzy Sets and Systems - Special issue on Uncertainty in geographic information systems and spatial data
Heuristics for Solving Fuzzy Constraint Satisfaction Problems
ANNES '95 Proceedings of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems
CHINZ '06 Proceedings of the 7th ACM SIGCHI New Zealand chapter's international conference on Computer-human interaction: design centered HCI
Ambient Compass: One Approach to Model Spatial Relations
ICDHM '09 Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009
Fuzzy approach to non-metric similarity indexing
Proceedings of the Fourth International Conference on SImilarity Search and APplications
Membership functions for spatial proximity
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Reasoning about shadows in a mobile robot environment
Applied Intelligence
The distance of probabilistic fuzzy sets for classification
Pattern Recognition Letters
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Most computer systems that deal with issues of space reason about distance by using a metric. For example, most geographic information systems apply the euclidean metric, requiring all subjects to adhere to the same view of space. As a result, dealing with imprecise or uncertain geographic information becomes difficult or sometimes even impossible. In this paper, we describe a way of reasoning about distance that is not restricted to euclidean geometry. The idea is to use fuzzy sets to describe how close objects are to each other.