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    An Influence Maximization Algorithm Based on the Influence Propagation Range of Nodes

    Yong Hua1,Bolun Chen1,2,∗,Yan Yuan1, Guochang Zhu1, Fenfen Li1

    Journal on Internet of Things, Vol.1, No.2, pp. 77-88, 2019, DOI:10.32604/jiot.2019.05941

    Abstract The problem of influence maximization in the social network G is to find k seed nodes with the maximum influence. The seed set S has a wider range of influence in the social network G than other same-size node sets. The influence of a node is usually established by using the IC model (Independent Cascade model) with a considerable amount of Monte Carlo simulations used to approximate the influence of the node. In addition, an approximate effect (1-1/e) is obtained, when the number of Monte Carlo simulations is 10000 and the probability of propagation is very small. In this paper,… More >

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