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Auteur S. Sen |
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Framework for probabilistic geospatial ontologies / S. Sen in International journal of geographical information science IJGIS, vol 22 n° 6-7 (june 2008)
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Titre : Framework for probabilistic geospatial ontologies Type de document : Article/Communication Auteurs : S. Sen, Auteur Année de publication : 2008 Article en page(s) : pp 825 - 846 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] accès aux données localisées
[Termes IGN] base de données localisées
[Termes IGN] classification bayesienne
[Termes IGN] inférence
[Termes IGN] ontologie
[Termes IGN] OWL
[Termes IGN] référentiel sémantique
[Termes IGN] réseau routierRésumé : (Auteur) Partial knowledge about geospatial categories is important for practical use of ontologies in the geospatial domain. Degree of overlaps between geospatial categories, especially those based on geospatial actions concepts and geospatial enitity concepts, need to be specified in ontologies. Conventional geospatial ontologies do not enable specification of such information, and this presents difficulties in ontology reasoning for practical purposes. We present a framework to encode probabilistic information in geospatial ontologies based on the BayesOWL approach. The approach enables rich inferences such as most similar concepts within and across ontologies. This paper presents two case studies of using road-network ontologies to demonstrate the framework for probabilistic geospatial ontologies. Besides inferences within the probabilistic ontologies, we discuss inferences about most similar concepts across ontologies based on the assumption that geospatial action concepts are invariable. The results of such machine-based mappings of most similar concepts are verified with mappings of concepts extracted from human subjects testing. The practical uses of probabilistic geospatial ontologies for concept matching and measuring naming heterogeneities between two ontologies are discussed. Based on our experiments, we propose such a framework for probabilistic geospatial ontologies as an advancement of the proposal to develop semantic reference systems. Copyright Taylor & Francis Numéro de notice : A2008-234 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701694853 En ligne : https://doi.org/10.1080/13658810701694853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29229
in International journal of geographical information science IJGIS > vol 22 n° 6-7 (june 2008) . - pp 825 - 846[article]Exemplaires(2)
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