Toward understanding the mobile Internet user behavior: a methodology for user clustering with aging analysis

The mobile Internet emergence gives a new class of opportunities to analyze the user behavior in the environment that is closely related to the users´ real lives. The rapid growth in the wireless Internet has a significant dynamic nature, which leads to the difficulty of stable analysis. It is common to witness the drastic traffic change in the mobile Internet. It is important to identify the dynamic transitions of use patterns. User tracking is possible to use the user identifier commonly used in the mobile Internet. From the long-term observation of mobile Internet user transaction logs based on the user identifier, we analyze the long-term usage pattern to identify the metrics to segment various mobile Internet user behaviors. The proposed method uses the number of months in which an end user shows continuous use. The results from the case study and future issues are presented.