4.6 Article

C-3PO: Click-sequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation I know you'll click

Journal

SOFT COMPUTING
Volume 23, Issue 22, Pages 11793-11799

Publisher

SPRINGER
DOI: 10.1007/s00500-018-03730-5

Keywords

Click sequence aware; Deep learning; Deep neural network

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With the emergence of mobile and wearable devices, push notification becomes a powerful tool to connect and maintain the relationship with app users, but sending inappropriate or too many messages at the wrong time may result in the app being removed by the users. In order to maintain the retention rate and the delivery rate of advertisement, we adopt deep neural network (DNN) to develop a pop-up recommendation system Click-sequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation (C-3PO) enabled by collaborative filtering-based hybrid user behavioral analysis. We further verified the system with real data collected from the product security master, clean master, and CM browser, supported by Leopard Mobile Inc. (Cheetah Mobile Taiwan Agency). In this way, we can know precisely about users' preference and frequency to click on the push notification/pop-ups, decrease the troublesome to users efficiently, and meanwhile increase the click-through rate of push notifications/pop-ups.

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