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The user behavior analysis of the mobile Internet is still to be explored. This increases importance in research and business as the mobile Internet penetration becomes visible. The author performs a preparatory survey to identify the user behavior scenarios during a day. It indicates that there are three distinguished mobile Internet behavior patterns: (a) always active, (b) irregular, (c) prime time use. This gives a novel perspective to understand user interactions in the mobile Internet. Intelligent mobile services require addressing these differences in order to improve user experience. The author proposes a user-perceived freshness method to cluster users with the content access logs in order to utilize this three-subgroup-based view. The revisit ratio in the following month is used to characterize the user clusters and the middle users show a high revisit ratio. The author discusses the characteristics of this middle user segment.