A survey on influence maximization: From an ml-based combinatorial optimization

Y Li, H Gao, Y Gao, J Guo, W Wu - ACM Transactions on Knowledge …, 2023 - dl.acm.org
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 …

Guided genetic algorithm for the influence maximization problem

P Krömer, J Nowaková - … Conference, COCOON 2017, Hong Kong, China …, 2017 - Springer
Influence maximization is a hard combinatorial optimization problem. It requires the
identification of an optimum set of k network vertices that triggers the activation of a …

Multiple influence maximization in social networks

H Sun, X Gao, G Chen, J Gu, Y Wang - Proceedings of the 10th …, 2016 - dl.acm.org
Influence Maximization, a technique of social analysis to help marketers select a small group
of users to promote their products with the goal of maximizing their influence spread, has …

Efficient and effective influence maximization in social networks: a hybrid-approach

YY Ko, KJ Cho, SW Kim - Information Sciences, 2018 - Elsevier
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 …

Staticgreedy: solving the scalability-accuracy dilemma in influence maximization

S Cheng, H Shen, J Huang, G Zhang… - Proceedings of the 22nd …, 2013 - dl.acm.org
Influence maximization, defined as a problem of finding a set of seed nodes to trigger a
maximized spread of influence, is crucial to viral marketing on social networks. For practical …

An issue in the martingale analysis of the influence maximization algorithm imm

W Chen - Computational Data and Social Networks: 7th …, 2018 - Springer
This paper explains a subtle issue in the martingale analysis of the IMM algorithm, a state-of-
the-art influence maximization algorithm. Two workarounds are proposed to fix the issue …

Efficient influence maximization in social networks

W Chen, Y Wang, S Yang - Proceedings of the 15th ACM SIGKDD …, 2009 - dl.acm.org
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 …

LAIM: A linear time iterative approach for efficient influence maximization in large-scale networks

H Wu, J Shang, S Zhou, Y Feng, B Qiang, W Xie - IEEE Access, 2018 - ieeexplore.ieee.org
The problem of influence maximization (IM) has been extensively studied in recent years
and has many practical applications such as social advertising and viral marketing. Given …

Efficient algorithms for influence maximization in social networks

YC Chen, WC Peng, SY Lee - Knowledge and information systems, 2012 - Springer
In recent years, due to the surge in popularity of social-networking web sites, considerable
interest has arisen regarding influence maximization in social networks. Given a social …

DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks

L Cui, H Hu, S Yu, Q Yan, Z Ming, Z Wen… - Journal of Network and …, 2018 - Elsevier
Influence maximization (IM) is the problem of finding a small subset of nodes in a social
network so that the number of nodes influenced by this subset can be maximized. Influence …