Research on behavioral targeted advertising in mobile Internet

This paper designs and implements the advertising recommending system based on user behavior under mobile Internet. By analyzing the user's online behavior, user profile that includes long-term interests and short-term interests can be obtained. In the end of this paper, the similarity between the behavior clusters and the advertisements is calculated, which is used to rank and select the most appropriate advertisements. The experiments show that the system can push the appropriate advertisements according to the user's different interest