For the poor model generalization and low diagnostic efficiency of fault diagnosis under
imbalanced distributions, a novel fault diagnosis method using variational autoencoder …

Influence Maximization (IM) is a classical combinatorial optimization problem, which can be
widely used in mobile networks, social computing, and recommendation systems. It aims at …

Advertising using the word-of-mouth effect is quite effective in promoting products. In the last
decade, there has been intensive research studying the influence maximization problem in …

Balanced influence maximization aims to balance the influence maximization of multiple
different entities in social networks and avoid the emergence of filter bubbles and echo …

The influence maximization problem (IMP) has been one of the most attractive topics in the
field of social networks. However, sometimes fairness in IMP should be considered …

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 …

To aid in designing effective rumor control strategies, combined with system dynamics, the
paper proposed a ternary interaction evolutionary game model of participants of rumor and …

Influence maximization in social networks aims to identify users with the highest influence in
the network and leverage them as initial spreaders to maximize the revenue of influence …

Traditional prediction models of rumor forwarding are based solely on explicit network
topology, and with no consideration for homogeneity and antagonism among multi-type …

Identification of fundamental agents in interdependent networks with heterogeneous nodes
is a key and challenging topic. It is crucial to understand the topology and dynamic …