Abstract
The development and standardization of semantic web technologies have resulted in an unprecedented volume of RDF datasets being published on the Web. However, data quality exists in most of the information systems, and the RDF data is no exception. The quality of RDF data has become a hot spot of Web research and many data quality dimensions and metrics have been proposed. In this paper, we focus on the redundant problem in RDF data, and propose a rule based method to find and delete the semantic redundant triples. By evaluating the existing datasets, we prove that our method can remove the redundant triples to help data publisher provide more concise RDF data.
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Acknowledgement
This work was partially supported by a grant from the NSF (Natural Science Foundation) of China under grant number 60803160 and 61272110, the Key Projects of National Social Science Foundation of China under grant number 11&ZD189, and it was partially supported by a grant from NSF of Hubei Prov. of China under grant number 2013CFB334. It was partially supported by NSF of educational agency of Hubei Prov. under grant number Q20101110, and the State Key Lab of Software Engineering Open Foundation of Wuhan University under grant number SKLSE2012-09-07.
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Guang, T., Gu, J., Huang, L. (2016). Detect Redundant RDF Data by Rules. In: Gao, H., Kim, J., Sakurai, Y. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9645. Springer, Cham. https://doi.org/10.1007/978-3-319-32055-7_30
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DOI: https://doi.org/10.1007/978-3-319-32055-7_30
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