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.
CITATION STYLE
Potoniec, J. (2015). Knowledge Engineering and Knowledge Management. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8982, 225–232. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84928569438&partnerID=tZOtx3y1
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