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 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 …

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

With the wide adoption of mobile devices, it becomes increasingly important to understand
how users use mobile apps. Knowing when and where certain apps are used is instrumental …

The ability to predict human mobility, ie, transitions between a user's significant locations
(the home, workplace, etc.) can be helpful in a wide range of applications, including targeted …

Inferring socio-demographic attributes of users is an important and challenging task that
could help with personalization, recommendation, advertising, etc. Sensor data collected …

With increasing diversity of user interest and preference, personalized location
recommendation is essential and beneficial to our daily life. To achieve this, the most critical …

With the rapid development of Internet services and mobile devices, nowadays, users can
connect to online services anytime and anywhere. Naturally, user's online activity behavior …

The diversity of personal interest and preference of mobile users results in a wide spectrum
of mobile app usage, and it is important to predict such app preference in order to provide …

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 …