Local Probability Solution Based Immune Genetic Influence Maximization Algorithm

The problem of influence maximization is to select a small number of users in a complex social network to maximize the diffusion of influence under a specific propagation model. The greedy Monte Carlo simulation approach theoretically guarantees a near-optimal solution, but it is very inefficient. A...
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Saved in:
Author:

QIAN Fulan, XU Tao, ZHAO Shu, ZHANG Yanping [VerfasserIn]

Format:

Electronic Article

Language:

Chinese

Published:

2020

Subjects:

social network

in uence maximization

monte carlo simulation

immune genetic

Electronic computers. Computer science

QA75.5-76.95

Containing Work:

In: Jisuanji kexue yu tansuo - Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press, 2021, 14(2020), 5, Seite 783-791

Containing Work:

volume:14 ; year:2020 ; number:5 ; pages:783-791

Links:

https://doi.org/10.3778/j.issn.1673-9418.1905010 [kostenfrei]

https://doaj.org/article/fcf4a33938e74279bcab7c88fc1a8c30 [kostenfrei]

http://fcst.ceaj.org/CN/abstract/abstract2191.shtml [kostenfrei]

Journal toc [kostenfrei]

DOI / URN:

10.3778/j.issn.1673-9418.1905010

Catalog id:

DOAJ068406118

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