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 ensure user satisfaction and success of mobile applications, it is important to provide
highly performant applications. This is particularly important for resource-constrained …

Mobile and IoT scenarios increasingly involve interactive and computation intensive
contextual recognition. Existing optimizations typically resort to computation offloading or …

Given the large number of installed apps and the limited screen size of mobile devices, it is
often tedious for users to search for the app they want to use. Although some mobile OSs …

Real-life mobile phone data may contain noisy instances, which is a fundamental issue for
building a prediction model with many potential negative consequences. The complexity of …

Smartphones can collect considerable context data about the user, ranging from apps used
to places visited. Frequent user patterns discovered from longitudinal, multi-modal context …

In this paper we present the first population-level, city-scale analysis of application usage on
smartphones. Using deep packet inspection at the network operator level, we obtained a …

Third party apps are an integral component of the smartphone ecosystem. In this paper, we
investigate how user traits can be inferred by observing only a single snapshot of installed …

Smartphones nowadays have become indispensable personal gadgets to support our
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …

This paper aims to predict the apps a user will open on her mobile device next. Such an
information is essential for many smartphone operations, eg, app pre-loading and content …