In this paper, we study how to activate a specific set of targeting users T, e.g., selling a product to a specific target group, is a practical problem for using the limited budget efficiently. To address this problem, we first propose the Activation Probability Maximization (APM) problem, i.e., to select a seed set S such that the activation probability of the target users in T is maximized. Considering that the influence will decay during information propagation, we propose a novel and practical Influence Decay Model (IDM) as the information diffusion model in the APM problem. Based on the IDM, we show that the APM problem is NP-hard and the objective function is monotone non-decreasing and submodular. We provide a ((1 − 1/e)-approximation Basic Greedy Algorithm (BGA). Furthermore, a speed-up Scalable Algorithm (SA) is proposed for online large social networks. Finally, we run our algorithms by simulations on synthetic and real-life social networks to evaluate the effectiveness and efficiency of the proposed algorithms. Experimental results validate our algorithms are superior to the comparison algorithms.
CITATION STYLE
Yan, R., Li, Y., Li, D., Zhu, Y., Wang, Y., & Du, H. (2019). Activation Probability Maximization for Target Users Under Influence Decay Model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11653 LNCS, pp. 603–614). Springer Verlag. https://doi.org/10.1007/978-3-030-26176-4_50
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