Smartphone app usage analysis: datasets, methods, and applications
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …
users has increased dramatically over the last decade. These personal devices, which are …
A survey of performance optimization for mobile applications
To ensure user satisfaction and success of mobile applications, it is important to provide
highly performant applications. This is particularly important for resource-constrained …
highly performant applications. This is particularly important for resource-constrained …
Predicting the next app that you are going to use
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 …
often tedious for users to search for the app they want to use. Although some mobile OSs …
Foggycache: Cross-device approximate computation reuse
Mobile and IoT scenarios increasingly involve interactive and computation intensive
contextual recognition. Existing optimizations typically resort to computation offloading or …
contextual recognition. Existing optimizations typically resort to computation offloading or …
A machine learning based robust prediction model for real-life mobile phone data
IH Sarker - Internet of Things, 2019 - Elsevier
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 …
building a prediction model with many potential negative consequences. The complexity of …
Mobileminer: Mining your frequent patterns on your phone
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 …
to places visited. Frequent user patterns discovered from longitudinal, multi-modal context …
Predicting user traits from a snapshot of apps installed on a smartphone
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 …
investigate how user traits can be inferred by observing only a single snapshot of installed …
Smartphone app usage prediction using points of interest
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 …
smartphones. Using deep packet inspection at the network operator level, we obtained a …
Mining smartphone data for app usage prediction and recommendations: A survey
H Cao, M Lin - Pervasive and Mobile Computing, 2017 - Elsevier
Smartphones nowadays have become indispensable personal gadgets to support our
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …
activities in almost every aspect of our lives. Thanks to the tremendous advancement of …
Individualized time-series segmentation for mining mobile phone user behavior
Mobile phones can record individual's daily behavioral data as a time-series. In this paper,
we present an effective time-series segmentation technique that extracts optimal time …
we present an effective time-series segmentation technique that extracts optimal time …