With the increasing development of social networks, they have turned into important
research platforms. Influence maximization is one of the most important research issues in …

Influence maximization (IM) problem, a fundamental algorithmic problem, is the problem of
selecting a set of k users (refer as seed set) from a social network to maximize the expected …

Influence maximization is a classic optimization problem to find a subset of seed nodes in a
social network that has a maximum influence with respect to a propagation model. This …

In recent years, due to the surge in popularity of social-networking web sites, considerable
interest has arisen regarding influence maximization in social networks. Given a social …

Influence maximization is the process of identifying a small set of influential nodes from a
complex network to maximize the number of activation nodes. Due to the critical issues such …

Influence maximization problem aims to find a set of nodes with the highest diffusion in
social networks in order to maximize diffusion in the graph by this set. A set of these nodes …

Influence maximization is an optimization problem in the area of social graph analysis,
which asks to choose a subset of k individuals to maximize the number of influenced nodes …

Influence maximization, ie to maximize the influence spread in a social network by finding a
group of influential nodes as small as possible, has been studied widely in recent years …

This paper aims to effectively solve the problem of the influence maximization in social
networks. For this purpose, an influence maximization method that can identify influential …

Influence Maximization (IM) is a key algorithmic problem that has been extensively studied
in social influence analysis, but most of existing researches either make sacrifices in solution …