Hybrid geo-spatial query methods on the semantic web with a spatially-enhanced index of DBpedia

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Abstract

Semantic Web resources such as DBpedia provide a rich source of structured knowledge about geographical features such as towns, rivers and historical buildings. Retrieval from these resources of all content that is relevant to a particular spatial query of, for example, containment or proximity is not always straightforward because there is considerable inconsistency in the way in which geographical features are referenced to location. In DBpedia some geographical feature instances have point coordinates, some have qualitative properties that provide explicit or implicit locational information via place names, and some have neither of these. Here we show how structured geo-spatial query, a form of question answering, on DBpedia can be performed with a hybrid strategy that exploits both quantitative and qualitative spatial properties in combination with a high quality reference geo-dataset that can help to support a full range of geo-spatial query operators. © 2012 Springer-Verlag.

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Younis, E. M. G., Jones, C. B., Tanasescu, V., & Abdelmoty, A. I. (2012). Hybrid geo-spatial query methods on the semantic web with a spatially-enhanced index of DBpedia. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7478 LNCS, pp. 340–353). https://doi.org/10.1007/978-3-642-33024-7_25

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