Influence maximization (IM) is the problem of finding a small subset of nodes (seed nodes)
in a social network that could maximize the spread of influence. Despite the progress …

Influence maximization (im) is the problem of finding a small subset of nodes (seed nodes)
in a social network that could maximize the spread of influence. Despite the progress …

Influence Maximization (IM) is the problem of finding a seed set composed of k nodes that
maximize their influence spread over a social network. Kempe et al. showed the problem to …

Influence maximisation (IM) is the problem of finding a set of k-seed nodes that could
maximize the amount of influence spread in a social network. In this article, we point out that …

Influence Maximization aims to find the top-K influential individuals to maximize the
influence spread within a social network, which remains an important yet challenging …

Influence maximization (IM) is the problem of identifying k most influential users (seed) in
social networks to maximize influence spread. Despite some recent development achieved …

Influence Maximization is an extensively-studied problem that targets at selecting a set of
initial seed nodes in the Online Social Networks (OSNs) to spread the influence as widely as …

Influence maximization (IM) is a classic problem, which aims to find a set of k users (called
seed set) in a social network such that the expected number of users influenced by the seed …

Influence Maximization (IM) plays an essential role in various social network applications.
One such application is viral marketing to trigger a large cascade of product adoption from a …

Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a
social network that could maximize the spread of influence. In this paper, we study the …