Affiliations: [a]
Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore, India
| [b]
Department of Mathematics, Tamralipta Mahavidyalaya, Tamluk, West Bengal, India
| [c] Faculty of Science and Technology, University of the Faroe Islands, Tórshavn, Faroe Islands
Correspondence:
[*]
Corresponding author. Sovan Samanta, Department of Mathe-matics, Tamralipta Mahavidyalaya, Tamluk, West Bengal – 721636, India E-mail: [email protected].
Abstract: Prediction of links/ connections in social networks is useful for increasing business in the area of telecom and social media. All types of social networking organization are trying to increase their nodes, i.e. the number of members. So the calculation of link prediction is the most important task because this calculation will help how to increase the number of user on a social network. A new technique of link prediction, namely RSM index, is introduced in this paper. Few essential properties have been established. Also, a comparative study with the existing methods is depicted with suitable tables and graphs.
Keywords: Social Network, link prediction, fuzzy networks, RSM index
