Future link regression using supervised learning on graph topology
نویسندگان
چکیده
Link prediction provides useful information for a variety of graph models, including communication, biochemical, and social networks. The goal of link prediction is usually to predict novel interactions (modeled as links/edges) between previously unconnected nodes in a graph. Link prediction is used on social networks to suggest future friends and in protein networks to suggest possible undiscovered pairwise interactions. Link prediction does not model repeat interactions or make any predictions about the number of interactions. To do this we need to predict the weight of links. We call this this problem link regression.
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