Efficient Distance Aware Influence Maximization in Geo Social Networks
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As the proliferation of geo-social networks, location-aware promotion is becoming more necessary in real applications. In this paper, we study the distance-aware influence maximization (DAIM) problem, which advocates the importance of the distance between users and the promoted location. The propagation of influence is based on the trust between families, close friends, etc, this marketing strategy is shown to be more effective than the traditional advertising channels, such as TV and newspapers. Unlike the traditional influence maximization problem, DAIM treats users differently based on their distances from the promoted location. Finally, we demonstrate the efficiency and effectiveness of proposed methods over real geo-social networks
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