Maintaining knowledge about temporal intervals
Communications of the ACM
Language and Spatial Cognition
Language and Spatial Cognition
Qualitative representation of spatial knowledge in two-dimensional space
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Using Orientation Information for Qualitative Spatial Reasoning
Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
Consistent Queries over Cardinal Directions Across Different Levels of Detail
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Composing cardinal direction relations
Artificial Intelligence
Toward heterogeneous cardinal direction calculus
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
A linguistic ontology of space for natural language processing
Artificial Intelligence
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Modeling human concepts of object locations is essential for the development of the systems and machines that collaborate with ordinary people on spatial tasks. This paper applies a heterogeneous cardinal direction model, called HCDM, to model human concepts of object locations on a plane, using its ability to illustrate where and how an object is located as seen from another with different spatial extensions. For generality, we adopt a set of formal spatial concepts defined in an existing spatial ontology called GUM. These location concepts are associated with the patterns distinguished by HCDM. We also discuss the special features of our modeling approach and compare it with the modeling of location concepts by other cardinal direction models.