Metric details for natural-language spatial relations
ACM Transactions on Information Systems (TOIS)
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
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GeoS'05 Proceedings of the First international conference on GeoSpatial Semantics
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GeoS'07 Proceedings of the 2nd international conference on GeoSpatial semantics
Evaluation of a semantic similarity measure for natural language spatial relations
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Affordance-based similarity measurement for entity types
COSIT'07 Proceedings of the 8th international conference on Spatial information theory
The effect of context on semantic similarity measurement
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The influence of scale, context and spatial preposition in linguistic topology
SC'06 Proceedings of the 2006 international conference on Spatial Cognition V: reasoning, action, interaction
Geographic ontology matching with iG-match
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Semantic referencing - determining context weights for similarity measurement
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Hybrid model for semantic similarity measurement
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
A new benchmark dataset with production methodology for short text semantic similarity algorithms
ACM Transactions on Speech and Language Processing (TSLP)
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Measuring semantic similarity among concepts is the core method for assessing the degree of semantic interoperability within and between ontologies. In this paper, we propose to extend current semantic similarity measures by accounting for the spatial relations between different geospatial concepts. Such integration of spatial relations, in particular topologic and metric relations, leads to an enhanced accuracy of semantic similarity measurements. For the formal treatment of similarity the theory of conceptual vector spaces—sets of quality dimensions with a geometric or topologic structure for one or more domains—is utilized. These spaces allow for the measurement of semantic distances between concepts. A case study from the geospatial domain using Ordnance Survey's MasterMap is used to demonstrate the usefulness and plausibility of the approach.