The influence maximization (IM) problem identifies the subset of influential users in the
network to provide solutions for real-world problems like outbreak detection, viral marketing …

Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …

To meet the requirement of social influence analytics in various applications, the problem of
influence maximization has been studied in recent years. The aim is to find a limited number …

Influence maximization (IM) is the process of choosing a set of seeds from a social network
so that the most individuals will be influenced by them. Calculating the social effect of a …

Influence maximization in social networks aims to find a small group of individuals, which
have maximal influence cascades. In this study, an optimization model based on a local …

Software-defined vehicular network (SDVN) is a promising networking paradigm that can
provide intelligent information exchanges by separating network management and data …

Influence Maximization is an important problem in social networks, and its main goal is to
select some most influential initial nodes (ie, seed nodes) to obtain the maximal influence …

Influence maximization is to extract a small set of nodes from a social network which
influences the propagation maximally under a cascade model. In this paper, we propose a …

Influence maximization, defined as finding a small subset of nodes that maximizes spread of
influence in social networks, is NP-hard under both Independent Cascade (IC) and Linear …

In order to find the nodes with better propagation ability, a large body of studies on the
influence maximization problem has been conducted. Several influence spreading models …