Vertex cover preprocessing for influence maximization algorithms

M. Rostamnia, S. Kianian
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Abstract

The Influence maximization problem is a fundamental problem in social networks analysis which aims to select a small set of nodes, as a seed set, and maximizes influence spread through the seed set under a specific propagation model. In this paper, the effect of performing vertex cover, as a preprocess, has been investigated on the influence maximization algorithms under the independent cascade model. Proposed method eliminates ineffective nodes from the main calculation process to find the most influential nodes. Based on the results, combining the proposed algorithm with several methods on real-world datasets confirms the efficiency of the method.
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影响最大化算法的顶点覆盖预处理
影响力最大化问题是社会网络分析中的一个基本问题,其目的是在特定的传播模型下,选择一小部分节点作为种子集,并通过种子集使影响力传播最大化。本文研究了独立级联模型下,顶点覆盖作为一种预处理对影响最大化算法的影响。该方法从主计算过程中剔除无效节点,寻找影响最大的节点。在实际数据集上,将该算法与几种方法相结合,验证了该方法的有效性。
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