Due to the increasing popularity of recent advanced features and context-awareness in
smart mobile phones, the contextual data relevant to users' diverse activities with their …

Nowadays, machine learning classification techniques have been successfully used while
building data-driven intelligent predictive systems in various application areas including …

This paper mainly formulates the problem of predicting context-aware smartphone apps
usage based on machine learning techniques. In the real world, people use various kinds of …

This paper formulates the problem of building a context-aware predictive model based on
user diverse behavioral activities with smartphones. In the area of machine learning and …

Due to the advanced features in recent smartphones and context-awareness in mobile
technologies, users' diverse behavioral activities with their phones and associated contexts …

Smartphones are considered as one of the most essential and highly personal devices of
individuals in our current world. Due to the popularity of context-aware technology and …

This paper formulates the problem of a rule-based machine learning method to discover the
behavioral rules of individual smartphone users to provide context-aware intelligent …

In recent years, the importance of user information has increased rapidly for context-aware
applications. This paper proposes a deep learning mechanism to identify the transportation …

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 …

Predicting Apps usage has become an important task due to the proliferation of Apps, and
the complex of Apps. However, the previous research works utilized a considerable number …