Characterizing and predicting mobile application usage

Characterizing and predicting mobile application usage

In this paper, we propose data clustering techniques to predict temporal characteristics of data consumption behavior of different mobile applications via wireless communications. While most of the research on mobile data analytics focuses on the analysis of call data records and mobility traces, our analysis concentrates on mobile application usages, to characterize them and predict their beha...

Understanding and supporting mobile application usage

In recent years mobile phones have evolved significantly. While the very first cellular phones only provided functionality for conducting phone calls, smartphones nowadays provide a rich variety of functionalities. Additional hardware capabilities like new sensors (e.g. for location) and touch screens as new input devices gave rise to new use cases for mobile phones, such as navigation support,...

Prediction for Mobile Application Usage Patterns

Advances in smartphone technology have enabled the prevalence of mobile applications. Such a variety of mobile applications make the smartphone more interesting and more humanized, and running these applications has become the major function of smartphones. However, the limited resources of current smartphone requires both researchers and companies paying more attention to the way of effectivel...

Characterizing and Predicting Enhancers

Characterizing the functions of sequences in the human genome is crucial for the study and treatment of human disease. Though it is known that approximately 5% of the human genome is conserved, about 40% of these sequences have yet to be characterized, many of which may be important players in human disease pathways (1). Experimental and computational techniques have been developed which use hi...

Perceived security and usage of a mobile payment application