Managing big data by directed graph node similarity

E. Pap, Marko Jocic, Aniko Szakal, Djordje Obradovic, Zora Konjovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationCINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages25-30
Number of pages6
ISBN (Electronic)9781509039098
DOIs
Publication statusPublished - Feb 7 2017
Event17th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2016 - Budapest, Hungary
Duration: Nov 17 2016Nov 19 2016

Other

Other17th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2016
CountryHungary
CityBudapest
Period11/17/1611/19/16

Fingerprint

Directed graphs
Fuzzy sets
Directed Graph
Vertex of a graph
Social Networks
Fuzzy Sets
Big data
Similarity

ASJC Scopus subject areas

  • Control and Optimization
  • Artificial Intelligence
  • Information Systems

Cite this

Pap, E., Jocic, M., Szakal, A., Obradovic, D., & Konjovic, Z. (2017). Managing big data by directed graph node similarity. In CINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings (pp. 25-30). [7846374] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CINTI.2016.7846374

Managing big data by directed graph node similarity. / Pap, E.; Jocic, Marko; Szakal, Aniko; Obradovic, Djordje; Konjovic, Zora.

CINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 25-30 7846374.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pap, E, Jocic, M, Szakal, A, Obradovic, D & Konjovic, Z 2017, Managing big data by directed graph node similarity. in CINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings., 7846374, Institute of Electrical and Electronics Engineers Inc., pp. 25-30, 17th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2016, Budapest, Hungary, 11/17/16. https://doi.org/10.1109/CINTI.2016.7846374
Pap E, Jocic M, Szakal A, Obradovic D, Konjovic Z. Managing big data by directed graph node similarity. In CINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 25-30. 7846374 https://doi.org/10.1109/CINTI.2016.7846374
Pap, E. ; Jocic, Marko ; Szakal, Aniko ; Obradovic, Djordje ; Konjovic, Zora. / Managing big data by directed graph node similarity. CINTI 2016 - 17th IEEE International Symposium on Computational Intelligence and Informatics: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 25-30
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