Sim-DL: Towards a semantic similarity measurement theory for the description logic ALCNR in geographic information retrieval

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Abstract

Similarity measurement theories play an increasing role in GIScience and especially in information retrieval and integration. Existing feature and geometric models have proven useful in detecting close but not identical concepts and entities. However, until now none of these theories are able to handle the expressivity of description logics for various reasons and therefore arc not applicable to the kind of ontologies usually developed for geographic information systems or the upcoming geospatial semantic web. To close the resulting gap between available similarity theories on the one side and existing ontologies on the other, this paper presents ongoing work to develop a context-aware similarity theory for concepts specified in expressive description logics such as ALCNR. © Springer-Verlag Berlin Heidelberg 2006.

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Janowicz, K. (2006). Sim-DL: Towards a semantic similarity measurement theory for the description logic ALCNR in geographic information retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4278 LNCS-II, pp. 1681–1692). Springer Verlag. https://doi.org/10.1007/11915072_74

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