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 …

Mobile application usage prediction aims to infer the possible applications (Apps) that a user
will launch next. It is critical for many applications, eg, system optimization and smartphone …

In this paper, we introduce MP-GT, a novel Graph Neural Network model that leverages
meta-path-guided optimization within the GCN-Transformer framework to enhance …

Nowadays the explosion of smartphone Apps has created a fertile ground to study behavior
of mobile users. In this paper, we utilize network footprint data (NFP) which consists of DPI …

Context-aware mobile application (App) usage prediction benefits a variety of applications
such as precise bandwidth allocation, App launch acceleration, etc. Prior works have …

The explosive increasing mobile Applications (Apps) have been attracting researchers and
developers to investigate user preferences on various mobile Apps. Understanding mobile …

Both app developers and service providers have strong motivations to understand when and
where certain apps are used by users. However, it has been a challenging problem due to …

Nowadays smartphone users have installed dozens or even hundreds of APPs on their
phones. Predicting APP usage not only helps the mobile phone system to speed up APP …

Predicting application usage is useful for offering personalized services, improving mobile
energy consumption, and mobile system resource management optimization. Currently …

App usage prediction is important for smartphone system optimization to enhance user
experience. Existing modeling approaches utilize historical app usage logs along with a …