Link Prediction in Social Networks by Neutrosophic Graph

Authors

Rupkumar Mahapatra^1, , Sovan Samanta^{2, *,} , Madhumangal Pal^1, , Qin Xin^3,

¹Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore, 721102, India

²Department of Mathematics, Tamralipta Mahavidyalaya, West Bengal, 721636, India

³Faculty of Science and Technology, University of the Faroe Islands, Tórshavn, 100, Faroe Islands

^*Corresponding author. Email: ssamantavu@gmail.com

DOI

10.2991/ijcis.d.201015.002How to use a DOI?

Keywords

Social network; Neutrosophic graph; Link prediction; Modified RSM index

Abstract

The computation of link prediction is one of the most important tasks on a social network. Several methods are available in the literature to predict links in networks and RSM index is one of them. The RSM index is applicable in the fuzzy environment and it does not incorporate the notion of falsity and indecency parameters which occur frequently in uncertain environments. In the present method, the behaviors of the common neighbor and the other parameters, like nature of job, location, etc., are considered. In this paper, more parameters are included in the RSM index for making it more flexible and realistic and it is best fitted in the neutrosophic environment. Many important properties are studied for this modified RSM index. A small network from Facebook is considered to illustrate the problem.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Rupkumar Mahapatra
AU  - Sovan Samanta
AU  - Madhumangal Pal
AU  - Qin Xin
PY  - 2020
DA  - 2020/10/24
TI  - Link Prediction in Social Networks by Neutrosophic Graph
JO  - International Journal of Computational Intelligence Systems
SP  - 1699
EP  - 1713
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.201015.002
DO  - 10.2991/ijcis.d.201015.002
ID  - Mahapatra2020
ER  -