Assessing Semantic Similarities among Geospatial Feature Class Definitions
Lecture notes in computer sciencePublished 1 January 1999
M. Andrea Rodríguez, Max J. Egenhofer, Robert D. Rugg
Citations80
SJR quartileQ2
SJR score0.35
SNIP0.55
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TL;DR
This paper presents an innovative approach to semantic similarity assessment by combining the advantages of two different strategies: feature-matching process and semantic distance calculation.
Abstract
The assessment of semantic similarity among objects is a basic requirement for semantic interoperability. This paper presents an innovative approach to semantic similarity assessment by combining the advantages of two different strategies: feature-matching process and semantic distance calculation. The model involves a knowledge base of spatial concepts that consists of semantic relations (is-a and part-whole) and distinguishing features (functions, parts, and attributes). By taking into consideration cognitive properties of similarity assessments, this model represents a cognitively plausible and computationally achievable method for measuring the degree of interoperability.
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