Link Prediction in Social Networks by Neutrosophic Graph
- 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 -