Smartphone app usage analysis: datasets, methods, and applications
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …
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
With the prevalence of smartphones, people have left abundant behavior records in
cyberspace. Discovering and understanding individuals' cyber activities can provide useful …
cyberspace. Discovering and understanding individuals' cyber activities can provide useful …
Understanding the long-term evolution of mobile app usage
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 …
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
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 …
Although significant effort has been made to understand mobile app usage, existing studies …
Semantic-aware spatio-temporal app usage representation via graph convolutional network
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 …
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
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 …
beneficial for user experience improvement. Through an in-depth analysis on a real-world …
Attentional Markov model for human mobility prediction
Accurate human mobility prediction is important for many applications in wireless networks,
including intelligent content caching and prefetching, network optimization, etc. However …
including intelligent content caching and prefetching, network optimization, etc. However …
Learning dynamic app usage graph for next mobile app recommendation
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 …
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
In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …
like app recommendation, user behaviour analysis, and mobile resource management …
Joint VNF placement, CPU allocation, and flow routing for traffic changes
The emerging network-softwarization technologies, such as software-defined networking
and network function virtualization play important roles in 5G communication and future …
and network function virtualization play important roles in 5G communication and future …