面向不确定性影响源的社会网络影响力传播抑制方法

发布时间：2018-05-15 11:24

本文选题：社会网络 + 不确定性影响源　；参考：《电子与信息学报》2017年09期

【摘要】：社会网络中影响力传播的有效抑制是社会网络影响力传播机制研究所关注的问题之一。该文针对未知影响传播源,或传播源信息具有不确定性的情况,提出面向不确定性影响源的影响力传播抑制问题。首先,为有效提高抑制算法的执行效率,讨论竞争线性阈值传播模型下影响源传播能力的近似估计方法,进而提出有限影响源情况下,期望抑制效果最大化的抑制种子集挖掘算法。其次,对于大尺寸不确定性影响源的情况,考虑算法运行效率和抑制效果之间的有效折中,提出基于抽样平均近似的期望抑制效果最大化的抑制种子集挖掘算法。最后,在真实的社会网络数据集上,通过实验测试验证了所提出方法的有效性。
[Abstract]:The effective suppression of influence transmission in social network is one of the issues concerned in the research of social network influence dissemination mechanism. In this paper, the problem of influence propagation suppression for uncertain influence sources is proposed in view of the uncertainty of unknown influence sources or the uncertainty of propagating source information. Firstly, in order to improve the performance efficiency of the suppression algorithm, the approximate estimation method for the source propagation ability under the competitive linear threshold propagation model is discussed. An algorithm for mining suppression seed sets with maximum expected suppression effect. Secondly, considering the effective trade-off between the efficiency of the algorithm and the suppression effect, an algorithm based on the sample average approximation is proposed to maximize the expected suppression effect. Finally, on the real data set of social network, the validity of the proposed method is verified by experimental test.
【作者单位】：云南大学软件学院;云南省软件工程重点实验室;云南大学信息学院;
【基金】：国家自然科学基金(61562091,61472345) 云南省应用基础研究计划,(2014FA023,2016FB110) 云南大学中青年骨干教师培养计划项目;云南大学青年英才培育计划(XT412003) 云南省软件工程重点实验室开放项目(2012SE303,2012SE205)~~
【分类号】：G206;TP393.09

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