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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Mining RDF Data for OWL2 RL Axioms
verfasst von : Yuanyuan Li, Huiying Li, Jing Shi
Erschienen in: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data
Verlag: Springer Singapore
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Abstract
The large amounts of linked data are a valuable resource for the development of semantic applications. However, these applications often meet the challenges posed by flawed or incomplete schema, which would lead to the loss of meaningful facts. Association rule mining has been applied to learn many types of axioms. In this paper, we first use a statistical approach based on the association rule mining to enrich OWL ontologies. Then we propose some improvements according to this approach. Finally, we describe the quality of the acquired axioms by evaluations on DBpedia datasets.