Abstract
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.
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Acknowledgement
This paper was supported by the National Natural Science Foundation of China (Nos. 61472345, 61402398, 61232002), Natural Science Foundation of Yunnan Province (Nos. 2014FA023, 2013FB010), Program for Innovative Research Team in Yunnan University (No. XT412011), Program for Excellent Young Talents of Yunnan University (No. XT412003), and the Research Foundation of the Educational Department of Yunnan Province (No. 2014C134Y).
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Wu, H., Zhang, Z., Yue, K., Zhang, B., Liu, W. (2016). Maximizing the Cooperative Influence Spread in a Social Network Oriented to Viral Marketing. In: Morishima, A., et al. Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9865. Springer, Cham. https://doi.org/10.1007/978-3-319-45835-9_1
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DOI: https://doi.org/10.1007/978-3-319-45835-9_1
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