Over the last decade, the paradigm of Linked Data has gained momentum. It is possible to leverage implicit knowledge from these data using a reasoner. Nevertheless, current methods for reasoning over linked data are well suited for small to medium datasets, and they fail at reaching the scale of the Web of Data. In this PhD thesis, we are interested in how distributed computing in the Cloud can help a linked data reasoner to scale. We present in this paper the early state of this thesis. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Chevalier, J. (2013). A linked data reasoner in the cloud. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7882 LNCS, pp. 722–726). Springer Verlag. https://doi.org/10.1007/978-3-642-38288-8_59
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