Abstract
With the development of social network, online marketing has become more popular and developed in an unprecedented scale. Viral marketing propagates influence through ‘word-of-mouth’ effect. As for development of viral marketing, it is critical to select a set of influential users in the network to propagate influence as much as possible with limited resources. In this chapter, we proposed a model called Preference-based Trust Independent Cascade Model. Based on the experimental results, the Preference-based Trust Independent Cascade Model is able to obtain better results than some traditional models. Comparing with other existing methods, such as trust-only approach and random selection approach, the proposed Preference-based Trust Independent Cascade Model considers both user preference and trust connectivity.
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Jiang, C., Li, W., Bai, Q., Zhang, M. (2017). Preference Aware Influence Maximization. In: Bai, Q., Ren, F., Fujita, K., Zhang, M., Ito, T. (eds) Multi-agent and Complex Systems. Studies in Computational Intelligence, vol 670. Springer, Singapore. https://doi.org/10.1007/978-981-10-2564-8_11
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DOI: https://doi.org/10.1007/978-981-10-2564-8_11
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