Semantic-aware spatio-temporal app usage representation via graph convolutional network

Y Yu, T Xia, H Wang, J Feng, Y Li - … of the ACM on Interactive, Mobile …, 2020 - dl.acm.org
Recent years have witnessed a rapid proliferation of personalized mobile Apps, which
poses a pressing need for user experience improvement. A promising solution is to model …

ATPP: A Mobile App Prediction System Based on Deep Marked Temporal Point Processes

K Yang, X Zhao, J Zou, W Du - ACM Transactions on Sensor Networks, 2023 - dl.acm.org
Predicting the next application (app) a user will open is essential for improving the user
experience, eg, app pre-loading and app recommendation. Unlike previous solutions that …

You are how you use apps: user profiling based on spatiotemporal app usage behavior

T Li, Y Li, M Zhang, S Tarkoma, P Hui - ACM Transactions on Intelligent …, 2023 - dl.acm.org
Mobile apps have become an indispensable part of people's daily lives. Users determine
what apps to use and when and where to use them based on their tastes, interests, and …

Sequence-Graph Fusion Neural Network for User Mobile App Behavior Prediction

Y Wang, R Jiang, H Liu, D Yin, X Song - Joint European Conference on …, 2023 - Springer
In recent years, mobile applications (apps) on smartphones have shown explosive growth.
Massive and diversified apps greatly affect user experience. As a result, user mobile app …

DeepApp: Predicting personalized smartphone app usage via context-aware multi-task learning

T Xia, Y Li, J Feng, D Jin, Q Zhang, H Luo… - ACM Transactions on …, 2020 - dl.acm.org
Smartphone mobile application (App) usage prediction, ie, which Apps will be used next, is
beneficial for user experience improvement. Through an in-depth analysis on a real-world …

Learning dynamic app usage graph for next mobile app recommendation

Y Ouyang, B Guo, Q Wang, Y Liang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Next mobile app recommendation aims to recommend the next app that a user is most likely
to use based on the user's app usage behaviors, which is beneficial for improving user …

Graph-based method for app usage prediction with attributed heterogeneous network embedding

Y Zhou, S Li, Y Liu - Future Internet, 2020 - mdpi.com
Smartphones and applications have become widespread more and more. Thus, using the
hardware and software of users' mobile phones, we can get a large amount of personal …

CAP: Context-aware app usage prediction with heterogeneous graph embedding

X Chen, Y Wang, J He, S Pan, Y Li… - Proceedings of the ACM on …, 2019 - dl.acm.org
Context-aware mobile application (App) usage prediction benefits a variety of applications
such as precise bandwidth allocation, App launch acceleration, etc. Prior works have …

A novel context-aware mobile application recommendation approach based on users behavior trajectories

K Zhu, Y Xiao, W Zheng, X Jiao, CH Hsu - IEEE Access, 2020 - ieeexplore.ieee.org
With the rapid development of mobile internet technology, mobile applications (apps) have
been rapidly popularized. To facilitate users' choice of apps, app recommendation is …

AppUsage2Vec: Modeling smartphone app usage for prediction

S Zhao, Z Luo, Z Jiang, H Wang, F Xu… - 2019 IEEE 35th …, 2019 - ieeexplore.ieee.org
App usage prediction, ie which apps will be used next, is very useful for smartphone system
optimization, such as operating system resource management, battery energy consumption …