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Maximizing the Cooperative Influence Spread in a Social Network Oriented to Viral Marketing

机译:最大化与以病毒营销为导向的社交网络传播的合作影响

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In many real-world situations, there exist two or more associated products, such as beer and nappy, mobile phone and mobile power pack, bed and mattress etc., in which consumers are likely to purchase these two or more associated products simultaneously. Thus, the associated products can be promoted at the same time, which implies cooperative influence spread of products in viral marketing. In this paper, we focus on maximizing the cooperative influence spread of associated products in a social network. First, we make use of a similarity model, abbreviated as SM, to generate the probabilities of edges. Then, we obtain the cooperative influence spread graph based on single influence spread graphs of these two products and the associated rule. Further, we propose independent cascade model with accepted probability (ICMAP) to describe the cooperative influence spread in a social network, and give an improved greedy algorithm to maximize the cooperative influence spread approximately. Experimental results show the effectiveness and feasibility of the proposed algorithm.
机译:在许多现实世界的情况下,存在两个或更多相关产品,例如啤酒和尿布,手机和移动电源组,床和床垫等,其中消费者可能同时购买这两个或更多个相关联的产品。因此,可以同时促进相关产品,这意味着在病毒营销中的产品的协同影响。在本文中,我们专注于最大化社交网络中相关产品的合作影响。首先,我们利用类似的模型,缩写为SM,以生成边缘的概率。然后,我们基于这两个产品的单一影响和相关规则的单一影响来获得协作影响扩展图。此外,我们提出了具有接受概率(ICMAP)的独立级联模型来描述社交网络中的协同影响,并提供改进的贪婪算法,以最大限度地传播合作影响。实验结果表明了所提出的算法的有效性和可行性。

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