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Pairwise interactions between objects can be modeled as a graph, which is a set of nodes and edges that each connect a pair of nodes. We consider the problem of predicting whether edges exist between nodes based on other pairs of nodes that we have observed. From a partially-observed graph we extract several neighbourhood and path features, then evaluate several machine learning algorithms for predicting whether edges will exist between unobserved nodes. K-Nearest Neighbours was found to be thedoi:10.14288/1.0343049 fatcat:pcvdgr2pobe4njo66srql6urc4