A matrix alignment approach for link prediction

Abstract

This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictive features of the link structure by aligning the adjacency matrix of a network with weighted similarity matrices computed from node attributes and neighborhood topological features. Experimental results on a variety of network data have demonstrated the effectiveness of this approach.