SciELO - Scientific Electronic Library Online

vol.12 issue2On Multicriteria Mixed Integer Linear Programming Based Tools for Location Problems-An Updated Critical Overview Illustrated with a Bicriteria DSS author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand




Related links

  • Have no similar articlesSimilars in SciELO


Computación y Sistemas

Print version ISSN 1405-5546


MORENO IBARRA, Marco Antonio  and  LEVACHKINE, Serguei. Semantic Similarity between Systems of Geographic Objects Applied to Generalization of Geospatial Data. Comp. y Sist. [online]. 2008, vol.12, n.2, pp.232-241. ISSN 1405-5546.

The thesis presents an approach to verify the consistency of generalized geospatial data at a conceptual level. The principal stages of proposed methodology are Analysis, Synthesis, and Verification. Analysis is focused on extracting the peculiarities of spatial relations by means of quantitative measures. Synthesis is used to generate a conceptual representation (ontology) that explicitly and qualitatively represents the relations between geospatial objects, resulting in tuples called herein semantic descriptions. Verification consists of a comparison between two semantic descriptions (description of source and generalized data): we measure the semantic distance (confusion) between ontology local concepts, generating three global concepts Equal, Unequal, and Equivalent. They measure the (in) consistency of generalized data: Equal and Equivalent - their consistency, while Unequal - an inconsistency. The method does not depend on coordinates, scales, units of measure, cartographic projection, representation format, geometric primitives, and so on. The approach is applied and tested on the generalization of two topographic layers: rivers and elevation contour lines (case of study).

Keywords : semantic similarity; generalization; ontology; geographic objects.

        · abstract in Spanish     · text in English     · English ( pdf )


Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License