Link Prediction in Social Networks

Thiswork presents link prediction similarity measures for social networks that exploitthe degree distribution of the networks. In the context of link prediction indense networks, the text proposes similarity measures based on Markov inequalitydegree thresholding (MIDTs), which only consider nodes whose degree is above a thresholdfor a possible link. Also presented are similarity measures based on cliques(CNC, AAC, RAC), which assign extra weight between nodes sharing a greater numberof cliques.