Smartphone app usage analysis: datasets, methods, and applications

T Li, T Xia, H Wang, Z Tu, S Tarkoma… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …

To what extent we repeat ourselves? Discovering daily activity patterns across mobile app usage

T Li, Y Li, MA Hoque, T Xia… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the prevalence of smartphones, people have left abundant behavior records in
cyberspace. Discovering and understanding individuals' cyber activities can provide useful …

Understanding the long-term evolution of mobile app usage

T Li, Y Fan, Y Li, S Tarkoma… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …

” what apps did you use?”: Understanding the long-term evolution of mobile app usage

T Li, M Zhang, H Cao, Y Li, S Tarkoma… - Proceedings of the web …, 2020 - dl.acm.org
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …

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 …

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 …

Attentional Markov model for human mobility prediction

H Wang, Y Li, D Jin, Z Han - IEEE Journal on Selected Areas in …, 2021 - ieeexplore.ieee.org
Accurate human mobility prediction is important for many applications in wireless networks,
including intelligent content caching and prefetching, network optimization, etc. However …

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 …

MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings

Y Khaokaew, H Xue, FD Salim - Proceedings of the ACM on Interactive …, 2024 - dl.acm.org
In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …

Joint VNF placement, CPU allocation, and flow routing for traffic changes

J Sun, F Liu, H Wang, DO Wu - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
The emerging network-softwarization technologies, such as software-defined networking
and network function virtualization play important roles in 5G communication and future …