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Adaptive Influence Maximization under General Feedback Models
[article]
2019
arXiv
pre-print
Influence maximization is a prototypical problem enabling applications in various domains, and it has been extensively studied in the past decade. The classic influence maximization problem explores the strategies for deploying seed users before the start of the diffusion process such that the total influence can be maximized. In its adaptive version, seed nodes are allowed to be launched in an adaptive manner after observing certain diffusion results. In this paper, we provide a systematic
arXiv:1902.00192v3
fatcat:w7i2wi34azejhnjbfvez5umw6y