The complexity of constraint satisfaction revisited
Artificial intelligence in perspective
A general method for spatial reasoning in spatial databases
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
SIAM Journal on Computing
Reasoning about Binary Topological Relations
SSD '91 Proceedings of the Second International Symposium on Advances in Spatial Databases
Qualitative and Topological Relationships in Spatial Databases
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Topological relationships between complex spatial objects
ACM Transactions on Database Systems (TODS)
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Comparing relations with a multi-holed region
COSIT'09 Proceedings of the 9th international conference on Spatial information theory
On the minimality and decomposability of constraint networks
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Exploiting qualitative spatial reasoning for topological adjustment of spatial data
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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Reasoning about space has been a considerable field of study both in Artificial Intelligence and in spatial information theory. Many applications benefit from the inference of new knowledge about the spatial relationships between spatial objects on the basis of already available and explicit spatial relationship knowledge that we call spatial (relationship) facts. Hence, the task is to derive new spatial facts from known spatial facts. A considerable amount of work has focused on reasoning about topological relationships (as a special and important subset of spatial relationships) between simple spatial objects like simple regions. There is a common consensus in the GIS and spatial database communities that simple regions are insufficient to model spatial reality and that complex region objects are needed that allow multiple components and holes. Models for topological relationships between complex regions have already been developed. Hence, as the next logical step, the goal of this paper is to develop a reasoning model for them. Further, no reasoning model considers changes of the spatial fact basis stored in a database between consecutive queries. We show that conventional modeling suffers from performance degradation when the database is frequently changing. Our model does not assume any geometric representation model or data structure for the regions. The model is also backward compatible, i.e., it is also applicable to simple regions.