Deep graph representation learning and optimization for influence maximization
Influence maximization (IM) is formulated as selecting a set of initial users from a social
network to maximize the expected number of influenced users. Researchers have made …
network to maximize the expected number of influenced users. Researchers have made …
[HTML][HTML] Influence maximization frameworks, performance, challenges and directions on social network: A theoretical study
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 …
network to provide solutions for real-world problems like outbreak detection, viral marketing …
Influence maximization on social graphs: A survey
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 …
network to maximize the expected number of influenced users (called influence spread), is a …
A survey on influence maximization in a social network
Given a social network with diffusion probabilities as edge weights and a positive integer k,
which k nodes should be chosen for initial injection of information to maximize the influence …
which k nodes should be chosen for initial injection of information to maximize the influence …
Influence maximization on temporal networks: a review
Influence maximization (IM) is an important topic in network science where a small seed set
is chosen to maximize the spread of influence on a network. Recently, this problem has …
is chosen to maximize the spread of influence on a network. Recently, this problem has …
A discrete shuffled frog-lea** algorithm to identify influential nodes for influence maximization in social networks
Influence maximization problem aims to select a subset of k most influential nodes from a
given network such that the spread of influence triggered by the seed set will be maximum …
given network such that the spread of influence triggered by the seed set will be maximum …
A two-stage VIKOR assisted multi-operator differential evolution approach for Influence Maximization in social networks
The impact of online social networking on daily life is extending beyond personal
boundaries, becoming a tool for financial activities and even public well-being. Interactions …
boundaries, becoming a tool for financial activities and even public well-being. Interactions …
Revisiting the stop-and-stare algorithms for influence maximization
Influence maximization is a combinatorial optimization problem that finds important
applications in viral marketing, feed recommendation, etc. Recent research has led to a …
applications in viral marketing, feed recommendation, etc. Recent research has led to a …