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Evolving Systems

, Volume 10, Issue 4, pp 629–634 | Cite as

Fuzzy and neutrosophic modeling for link prediction in social networks

  • Tran Manh TuanEmail author
  • Pham Minh Chuan
  • Mumtaz Ali
  • Tran Thi Ngan
  • Mamta Mittal
  • Le Hoang SonEmail author
Original Paper

Abstract

Some new similarity measures for link prediction based on fuzzy and neutrosophic environments are proposed. It aims to determine possible association between two objects in a social network represented by a graph including nodes and edges. It is widely used in various domains such as in the co-authorship network and protein-interaction systems. Similarity measure is an important tool for such the determination. Herein, some new fuzzy and neutrosophic measures are proposed accompanied with mathematical properties. The validation on the co-authorship network datasets demonstrates the efficiency of the proposed method.

Keywords

Co-authorship network Link prediction Social networks Fuzzy similarity measures Neutrosophic measures 

Notes

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Thuyloi UniversityHanoiVietnam
  2. 2.Hung Yen University of Technology and EducationHung YenVietnam
  3. 3.University of Southern QueenslandToowoombaAustralia
  4. 4.Govind Ballabh Pant Engineering CollegeNew DelhiIndia
  5. 5.VNU Information Technology Institute, Vietnam National UniversityHanoiVietnam

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