Link Prediction with Spatial and Temporal Consistency in Dynamic Networks.

A computer-implemented method executed by at least one processor for performing link prediction with spatial and temporal consistency by employing a time-dependent matrix factorization technique is presented. The method includes developing, at a plurality of timestamps, relational data of a sequence of network structures each including a plurality of nodes and learning, by the at least one processor, a feature vector of each node of the plurality of nodes of the sequence of network structures by concurrently optimizing a temporal fitting constraint and a network propagation constraint. The method further includes determining a network structure at each timestamp, determining evolutionary patterns at each timestamp, and predicting links in a future network structure based on an evolution of the sequence of network structures within a user-defined sliding window by reducing time complexities of finding neighbors of each node of the plurality of nodes of the sequence of network structures.