Performance Evaluation of Link Prediction Techniques Based on Fuzzy Soft Set and Markov Model

Link prediction in social networks represents a significant task in understanding the behavior and actions of users. There are various methods to it and some of them are Jaccard’s Coefficient, Common Neighbor, and Sorenson etc. These methods predict the link correctly but sacrifice with efficiency. The reasons behind this are discussed in this paper with two new methods of link prediction to improve the efficiency. These methods are based on fuzzy soft set and Markov model. We analyze that the proposed work predicts more accurately links as compared to existing methods.