Maximizing Social Network Influences Based on User Preferences

The rapid development of the Internet has made social network an important information dissemination platform. Although comprehensive research has been conducted on maximizing social network in the past few decades, users are usually modelled invariably as vertices in the graph, due to the lack of personal user data. However, the simple premises and assumptions ignore the differences between users. In this paper, we propose a diffusion model CMMI based on user preferences and diffusion enhancement. To access accurately user preferences, we propose to integrate user and product interactive information into social network. Then, we raise the issue of maximizing social network influence under diffusion model based on user preferences. Finally, we optimize the influence maximization algorithm. We conduct several experiments to prove the effectiveness of the algorithm on them. The experimental results show the superiority of our proposed algorithms.