Abstract
Various knowledge models are widely adopted nowadays and many areas are taking advantage of their existence. On one hand there are generic models, domain ontologies that are used in fields like AI and computer knowledge-aware systems in general; on the other hand there are very specific models that only come in use in very specific areas like software engineering or business analysis. In the domain of information extraction, so-called extraction ontologies are used to extract and semantically annotate data. The aim of this paper is to propose a method of authoring extraction ontologies by reusing other pre-existing knowledge models. Our priority is maintaining the consistence between the extracted data and the existing models.
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Nekvasil, M., Svátek, V., Labský, M. (2008). Transforming Existing Knowledge Models to Information Extraction Ontologies. In: Abramowicz, W., Fensel, D. (eds) Business Information Systems. BIS 2008. Lecture Notes in Business Information Processing, vol 7. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79396-0_10
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DOI: https://doi.org/10.1007/978-3-540-79396-0_10
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