One-path Relaxed Realtime Constraint Mobile User Classification Method in Mobile Clickstreams

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The mobile Internet has become increasingly visible in everyday life. As mobile Internet penetration leverages content business opportunities it is crucial to identify methodologies to fit mobile-specific demands. Regularity is one of the important measures to capture easy-come easy-go mobile users. It is known that users with multiple visits per day with a long interval in between have a higher likelihood of revisiting in the following month than other users. The author proposes a 3+1 bit method to incorporate this empirical law in order to cope with the two major mobile restrictions: distributed server environments and large data streams. The proposed method can be performed in a one-path manner with 32-bit word boundary-awareness for memory compaction. Experimental results show that the method is promising for identifying revisiting users under mobile-specific constraints.

The mobile Internet has become increasingly visible in everyday life. As mobile Internet penetration leverages content business opportunities, it is crucial to identify methodologies to fit mobile-specific demands. Regularity is one of the important measures to capture easy-come, easy-go mobile users. It is known that users with multiple visits per day with a long interval in between have a higher likelihood of revisiting in the following month than other users. The author proposes a 3+1 bit method to incorporate this empirical law in order to cope with the two major mobile restrictions: distributed server environments and large data streams. The proposed method can be performed in a one-path manner with 32-bit word boundary-awareness for memory compaction. Experimental results show that the method is promising for identifying revisiting users under mobile-specific constraints.

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