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The effects of social influence and homophily suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. Recently, Yin et al. [Yin et al. 2010a; 2010b] proposed an attribute-augmented social network model, which we call as Social-Attribute Network (SAN), to integrate network structure and node attributes to perform both link prediction and attribute inference. They focused on generalizing the random walk withdoi:10.1145/2594455 fatcat:3kvor2tzszegvdhnmoiwnyqaga