TY - JOUR
T1 - C-3PO
T2 - Click-sequence-aware deeP neural network (DNN)-based Pop-uPs recOmmendation: I know you’ll click
AU - Huang, Ton Ton Hsien De
AU - Kao, Hung Yu
N1 - Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85059515931&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059515931&partnerID=8YFLogxK
U2 - 10.1007/s00500-018-03730-5
DO - 10.1007/s00500-018-03730-5
M3 - Article
AN - SCOPUS:85059515931
SN - 1432-7643
VL - 23
SP - 11793
EP - 11799
JO - Soft Computing
JF - Soft Computing
IS - 22
ER -