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RDF data is growing exponentially and expanding rapidly from different sources everyday. Storing large-scale RDF data has been a matter of concern since the beginning of the Semantic Web. In the recent past, multiple approaches for storing RDF data have been suggested, ranging from simple storages to advanced methods like clustering predicates, which belong(More)
There has been a recent explosion in data as the number of RDF triples increases. With this increase, RDF datasets and their graph relationships become more complex. Accordingly, there is a need to store and handle these huge volumes of triples with highly desired scalability. Therefore, we attempt in this paper to bridge the gaps of the current RDF storage(More)
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