Managing big data using fuzzy sets by directed graph node similarity

Marko Jocic, Endre Pap, Anikó Szakál, Djordje Obradovic, Zora Konjovic

Research output: Contribution to journalArticle

13 Citations (Scopus)


This paper proposes a novel algorithm for discovering similar nodes in very large directed graphs, with millions of nodes with billions of connections, which is based on the fuzzy set theory. The required input is 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.

Original languageEnglish
Pages (from-to)183-200
Number of pages18
JournalActa Polytechnica Hungarica
Issue number2
Publication statusPublished - Jan 1 2017


  • Big data
  • Directed graph
  • Node similarity
  • Twitter

ASJC Scopus subject areas

  • Engineering(all)

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