Ontologies form the basis of the semantic web by providing knowledge on concepts, relations and instances. Unfortunately, the manual creation of ontologies is a time intensive and hence expensive task. This leads to the so-called knowledge acquisition bottleneck being a major problem for a more widespread adoption of the semantic web. Ontology learning tries to widen the bottleneck by supporting human knowledge engineers in creating ontologies. For this purpose, knowledge is extracted from existing data sources and is transformed into ontologies. So far, most ontology learning approaches are limited to very basic types of ontologies consisting of concept hierarchies and relations but do not use large amounts of the expressivity ontologies provide. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Fleischhacker, D. (2011). Enriching ontologies by learned negation or how to teach ontologies vegetarianism. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6643 LNCS, pp. 508–512). https://doi.org/10.1007/978-3-642-21064-8_44
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