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Heuristic search for optimizing diffusion of influence in a social network under the resource constraint

机译:在资源约束下优化社交网络中影响力扩散的启发式搜索

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The diffusion of influence in a social network has been recently investigated in various fields. In this paper, we study the problem of minimizing the expected complete influence time of a social network under the resource constraint. We focus on the case where the budget for influencing the initial target set of individuals is limited. The incremental chance model is adopted to characterize the diffusion of influence, and a lower bound for the expected complete influence time is presented. In order to solve the problem effectively, we modify the well-known heuristic search approach, the A* algorithm, and provide a series of strategies for designing the heuristic functions. Finally, we perform experiments to show that the proposed algorithm generally performs better than widely used trivial heuristic methods.
机译:最近在各个领域中研究了社交网络中影响力的扩散。在本文中,我们研究了在资源约束下使社交网络的预期完全影响时间最小化的问题。我们关注的情况是,影响个人初始目标群体的预算有限。采用增量机会模型来描述影响力的扩散,并给出了预期的完全影响时间的下界。为了有效解决该问题,我们修改了著名的启发式搜索方法A *算法,并提供了一系列设计启发式功能的策略。最后,我们进行实验以表明所提出的算法通常比广泛使用的平凡启发式方法具有更好的性能。

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