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 are 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 \(\mathcal ALCNR\).
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11915072_109.
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Janowicz, K. (2006). Sim-DL: Towards a Semantic Similarity Measurement Theory for the Description Logic \(\mathcal ALCNR\) in Geographic Information Retrieval. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. OTM 2006. Lecture Notes in Computer Science, vol 4278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11915072_74
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