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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Text Mining for Ontology Construction
verfasst von : Silke Rehme, Michael Schwantner
Erschienen in: Data Analysis, Machine Learning and Knowledge Discovery
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Abstract
In the research project NanOn: Semi-Automatic Ontology Construction—a Contribution to Knowledge Sharing in Nanotechnology an ontology for chemical nanotechnology has been constructed. Parts of existing ontologies like CMO and ChEBI have been incorporated into the final ontology. The main focus of the project was to investigate the applicability of text mining methods for ontology construction and for automatic annotation of scientific texts. For this purpose, prototypical tools were developed, based on open source tools like GATE and OpenNLP. It could be shown that text mining methods which extract significant terms from relevant articles support conceptualisation done manually and ensure a better coverage of the domain. The quality of the annotation depends mostly on the completeness of the ontology with respect to synonymous and specific linguistic expressions.