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2016 | OriginalPaper | Chapter

Mining RDF Data for OWL2 RL Axioms

Authors : Yuanyuan Li, Huiying Li, Jing Shi

Published in: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data

Publisher: 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.

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Metadata
Title
Mining RDF Data for OWL2 RL Axioms
Authors
Yuanyuan Li
Huiying Li
Jing Shi
Copyright Year
2016
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-3168-7_12

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