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Factor Analysis for Influence Maximization Problem in Social Networks

机译:社交网络影响力最大化问题的因子分析

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摘要

In recent years, researchers have paid more attention to influence maximization problem. This problem is firstly defined by Domingos and Richardson as follows: finding a small set of individuals in a social network that could maximize the spread of influence under certain influence cascade model. To solve this issue, researchers proposed different algorithms. However, in all of these algorithms, the size of the chosen individuals ¨C k, is assigned in advance. In this paper, we conduct a preliminary exploration on the relationship between the size of the chosen set and the corresponding influence spread. We propose two metrics to analyze the factor k. Then we further consider the performance metric of the chosen set, which can be described by the stability of the chosen set. Experimental results on two real social networks show the efficiency and necessity of our proposed metrics.
机译:近年来,研究人员更加关注影响最大化的问题。这个问题首先由Domingos和Richardson定义如下:在社交网络中找到一小组个体,这些个体可以在一定的影响级联模型下最大化影响力的传播。为了解决这个问题,研究人员提出了不同的算法。但是,在所有这些算法中,预先分配了所选个体的大小-C k。在本文中,我们对所选集合的大小与相应影响范围之间的关系进行了初步探索。我们提出两个指标来分析因子k。然后,我们进一步考虑所选集合的性能指标,这可以通过所选集合的稳定性来描述。在两个真实社交网络上的实验结果表明了我们提出的指标的有效性和必要性。

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