Metric details for natural-language spatial relations
ACM Transactions on Information Systems (TOIS)
Naive Semantics for Natural Language Understanding
Naive Semantics for Natural Language Understanding
A Cognitive Assessment of Topological Spatial Relations: Results from an Empirical Investigation
COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
A Small Set of Formal Topological Relationships Suitable for End-User Interaction
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Acquisition of a vernacular gazetteer from web sources
Proceedings of the first international workshop on Location and the web
International Journal of Geographical Information Science
A Model for Representing Topological Relations Between Simple Concave Regions
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Quantifying spatial prepositions: an experimental study
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
Hi-index | 0.00 |
Most approaches to the description of spatial relations for use in spatial querying attempt to describe a set of spatial relations that are universally understood by users. While this method has proved successful for expert users of geographic information, it is less useful for non-experts. Furthermore, while some work has implied the universal nature of spatial relations, a large amount of linguistic evidence shows that many spatial relations vary fundamentally across languages. Natural Semantic Metalanguage (NSM) is a body of linguistic research that has identified the few specific spatial relations that are universal across languages. We show how these spatial relations can be used to describe a range of more complex spatial relations, including some from non-Indo-European languages that cannot readily be described with the usual spatial operators. Thus we propose that NSM is a tool that may be useful for the development of the next generation of spatial querying tools, supporting multilingual environments with widely differing ways of talking about space.