A user selection method in advertising recommendations
Xiaoli Wu, Bo Xiao, Zhiqing Lin · 2009
User recommendation problem is important for mobile operators when they provide some new service to users. The traditional methods provide a low success rate. In this paper, we present a novel user selection method of advertising recommendation according to the maximal frequent items discovery theory. The experimental results demonstrate that our method can improve the success rate dramatically and reduce the amount of garbage advertisements.