NScale: neighborhood-centric large-scale graph analytics in the cloud

@article{Quamar2015NScaleNL,
  title={NScale: neighborhood-centric large-scale graph analytics in the cloud},
  author={Abdul Quamar and Amol Deshpande and Jimmy J. Lin},
  journal={The VLDB Journal},
  year={2015},
  volume={25},
  pages={125-150}
}
There is an increasing interest in executing complex analyses over large graphs, many of which require processing a large number of multi-hop neighborhoods or subgraphs. Examples include ego network analysis, motif counting, finding social circles, personalized recommendations, link prediction, anomaly detection, analyzing influence cascades, and others. These tasks are not well served by existing vertex-centric graph processing frameworks, where user programs are only able to directly access… CONTINUE READING
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