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- W2792428752 abstract "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." @default.
- W2792428752 created "2018-03-29" @default.
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- W2792428752 date "2018-02-28" @default.
- W2792428752 modified "2023-09-27" @default.
- W2792428752 title "Hybrid User Behavioral Analysis with Deep Neural Network for Notifications/Pop-ups Recommendation" @default.
- W2792428752 hasPublicationYear "2018" @default.
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