@inproceedings{e3264bd8093f48b9878453b7864f17ed,
title = "Effective Mobile Notification Recommendation Using Social Nature of Locations",
abstract = "This paper proposes a robust method of location-based mobile notification recommendation. Sending the right notifications at the right locations at the right time can boost user experience of mobile applications. 1.8 million users' notification opening data is collected from a mobile news application for 2 months and analyzed. First, a way of grouping locations into by the similarities in their function or social nature is described for notification recommendation. The autocorrelations of these localities are then identified based on user preferences for news categories in them, and the presence of significant statistical noise is shown. The true latent correlations between localities are identified by performing robust correlation estimation using random matrix theory techniques. Finally, an effectiveness constrained notification optimization scheme, SLEECR, is presented that shows improvement in average notification opening rate of users by up to 62%, and decrease in average notification response time of users by up to 19%.",
keywords = "Notification, big data, mobile application, news",
author = "Prasanta Saikia and James She",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 15th IEEE International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017 ; Conference date: 06-11-2017 Through 11-11-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/DASC-PICom-DataCom-CyberSciTec.2017.203",
language = "English",
series = "Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1265--1270",
booktitle = "Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017",
address = "United States",
}