International Journal of Man-Machine Studies
The importance of rough approximation for information retrieval
International Journal of Man-Machine Studies
Modelling topological and metrical properties in physical processes
Proceedings of the first international conference on Principles of knowledge representation and reasoning
The EGG/YOLK reliability hierarchy: semantic data integration using sorts with prototypes
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Sorites paradox and vague geographies
Fuzzy Sets and Systems - Special issue on Uncertainty in geographic information systems and spatial data
Imprecise reasoning in geographic information systems
Fuzzy Sets and Systems - Special issue on Uncertainty in geographic information systems and spatial data
Mining multiple-level spatial association rules for objects with a broad boundary
Data & Knowledge Engineering
A spatial model for complex objects with a broad boundary supporting queries on uncertain data
Data & Knowledge Engineering
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Principles and Applications
Imprecision in Finite Resolution Spatial Data
Geoinformatica
Geoinformatica
Approximate qualitative spatial reasoning
Spatial Cognition and Computation
Geographic Data Mining and Knowledge Discovery
Geographic Data Mining and Knowledge Discovery
Rough set spatial data modeling for data mining
International Journal of Intelligent Systems - Granular Computing and Data Mining
Information Sciences: an International Journal
Fuzzying GIS topological functions for GIR needs
Proceedings of the 2nd international workshop on Geographic information retrieval
A Study on the Driving Forces of Urban Expansion Using Rough Sets
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Data Mining Approaches for Geo-Spatial Big Data: Uncertainty Issues
International Journal of Organizational and Collective Intelligence
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Uncertainty management has been considered essential for real world applications, and spatial data and geographic information systems in particular require some means for managing uncertainty and vagueness. Rough sets have been shown to be an effective tool for data mining and uncertainty management in databases. The 9-intersection, region connection calculus (RCC) and egg-yolk methods have proven useful for modeling topological relations in spatial data. In this paper, we apply rough set definitions for topological relationships based on the 9-intersection, RCC and egg-yolk models for objects with broad boundaries. We show that rough sets can be used to express and improve on topological relationships and concepts defined with these models.