Managing big data by directed graph node similarity

@article{Pap2016ManagingBD,
  title={Managing big data by directed graph node similarity},
  author={Endre E. Pap and Marko Jocix0107 and Anikx00F3 Szakx00E1l and Djordje Obradovix0107 and Zora D. Konjovix0107},
  journal={2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI)},
  year={2016},
  pages={000025-000030}
}
This paper shows a novel algorithm based on the theory of fuzzy sets for discovering similar nodes in very large directed graphs (millions of nodes with billions of connections), if provided with a sample of representative nodes that are highly affiliated with some feature. This approach is practically verified on Twitter social network case study to discover influential Twitter users in the field of science. 

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