LAIM: A Linear Time Iterative Approach for Efficient Influence Maximization in Large-Scale Networks

LAIM: A Linear Time Iterative Approach for Efficient Influence Maximization in Large-Scale Networks

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 the network and diffusion model, IM aims to find an influential set of seed nodes so that targeting them as diffusion sour...

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Bibliographic Details
Main Authors: Hongchun Wu, Jiaxing Shang, Shangbo Zhou, Yong Feng, Baohua Qiang, Wu Xie
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Influence maximization
iterative algorithm
social networks analysis
information diffusion
computational complexity
Online Access:https://ieeexplore.ieee.org/document/8428631/

Internet

https://ieeexplore.ieee.org/document/8428631/

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