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 …
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 …
Multi-round influence maximization
In this paper, we study the Multi-Round Influence Maximization (MRIM) problem, where
influence propagates in multiple rounds independently from possibly different seed sets, and …
influence propagates in multiple rounds independently from possibly different seed sets, and …
PIANO: Influence maximization meets deep reinforcement learning
H Li, M Xu, SS Bhowmick, JS Rayhan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Since its introduction in 2003, the influence maximization (IM) problem has drawn significant
research attention in the literature. The aim of IM, which is NP-hard, is to select a set of users …
research attention in the literature. The aim of IM, which is NP-hard, is to select a set of users …
Influence maximization considering fairness: A multi-objective optimization approach with prior knowledge
H Gong, C Guo - Expert Systems with Applications, 2023 - Elsevier
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 …
field of social networks. However, sometimes fairness in IMP should be considered …
Efficiently targeted billboard advertising using crowdsensing vehicle trajectory data
Different from online promotion, the outdoor billboard advertising industry suffers from a lack
of audience-targeted delivery and quantitative dissemination evaluation, which undermine …
of audience-targeted delivery and quantitative dissemination evaluation, which undermine …
A survey on location-driven influence maximization
Influence Maximization (IM), which aims to select a set of users from a social network to
maximize the expected number of influenced users, is an evergreen hot research topic. Its …
maximize the expected number of influenced users, is an evergreen hot research topic. Its …
Influence maximization in real-world closed social networks
In the last few years, many closed social networks such as WhatsAPP and WeChat have
emerged to cater for people's growing demand of privacy and independence. In a closed …
emerged to cater for people's growing demand of privacy and independence. In a closed …
Efficient approximation algorithms for adaptive influence maximization
Given a social network G and an integer k, the influence maximization (IM) problem asks for
a seed set S of k nodes from G to maximize the expected number of nodes influenced via a …
a seed set S of k nodes from G to maximize the expected number of nodes influenced via a …
Rl4co: an extensive reinforcement learning for combinatorial optimization benchmark
We introduce RL4CO, an extensive reinforcement learning (RL) for combinatorial
optimization (CO) benchmark. RL4CO employs state-of-the-art software libraries as well as …
optimization (CO) benchmark. RL4CO employs state-of-the-art software libraries as well as …