Abstract
Ontology learning from texts has recently been proposed as a new technology helping ontology designers in the modelling process. Discovery of non–taxonomic relations is understood as the least tackled problem therein. We propose a technique for extraction of lexical entries that may give cue in assigning semantic labels to otherwise ‘anonymous’ relations. The technique has been implemented as extension to the existing Text-to-Onto tool, and tested on a collection of texts describing worldwide geographic locations from a tour–planning viewpoint.
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Kavalec, M., Maedche, A., Svátek, V. (2004). Discovery of Lexical Entries for Non-taxonomic Relations in Ontology Learning. In: Van Emde Boas, P., Pokorný, J., Bieliková, M., Štuller, J. (eds) SOFSEM 2004: Theory and Practice of Computer Science. SOFSEM 2004. Lecture Notes in Computer Science, vol 2932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24618-3_21
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DOI: https://doi.org/10.1007/978-3-540-24618-3_21
Publisher Name: Springer, Berlin, Heidelberg
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