As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …

In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …

In mobile scenarios, there is a need for general user representations to solve multiple target
tasks. However, there are some challenges in the related research (eg, difficulty in learning …

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 …

At present, most mobile App start-up prediction algorithms are only trained and predicted
based on single-user data. They cannot integrate the data of all users to mine the correlation …

Despite the rapid advancement of mobile applications, predicting app usage remains a
formidable challenge due to intricate user behaviours and ever-evolving contexts. To …

Predicting user click behavior and making relevant recommendations based on the user's
historical click behavior are critical to simplifying operations and improving user experience …

With the increasing diversity of mobile apps, users install many apps in their smartphones
and often use several apps together to meet a specific requirement. Because of the …

Predicting Next Application Most Likely Used, referred to as NAMLU, is a problem predicting
what application a user will use at the next using prediction model. In this study, we propose …