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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Towards Ontology Refinement by Combination of Machine Learning and Attribute Exploration
verfasst von : Jedrzej Potoniec
Erschienen in: Knowledge Engineering and Knowledge Management
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We propose a new method for knowledge acquisition and ontology refinement for the Semantic Web. The method is based on a combination of the attribute exploration algorithm from the formal concept analysis and active learning approach to machine learning classification task. It enables utilization of Linked Data during the process of an ontology refinement in a manner that it is possible to use remote SPARQL endpoints. We also report on a preliminary experimental evaluation and argue that our method is reasonable and useful.