Recurrent neural variational model for follower-based influence maximization.
Information Sciences(2020)
摘要
Influence Maximization, aiming at selecting a small set of seed users in a social network to maximize the spread of influence, has attracted considerable attention recently. Most of the existing influence maximization algorithms focus on the diffusion model of one single-entity, which assumes that only one entity is propagated by users in social network. However, the diffusion situations in real world social networks often involve multiple entities, competitive or complementary, spreading through the whole network, and are more complex than the situations of single independent entity.
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关键词
Recurrent neural network,Variational autoencoder,Influence diffusion,Social networks
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