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An Agglomerative-adapted Partition Approach for Large-scale Graphs
2019
International Journal of Librarianship (IJoL)
In recent years, an increasing number of knowledge bases have been built using linked data, thus datasets have grown substantially. It is neither reasonable to store a large amount of triple data in a single graph, nor appropriate to store RDF in named graphs by class URIs, because many joins can cause performance problems between graphs. This paper presents an agglomerative-adapted approach for large-scale graphs, which is also a bottom-up merging process. The proposed algorithm can partition
doi:10.23974/ijol.2019.vol4.1.106
fatcat:lxhzzyvterbrxajff65br3vz2e