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 …
Understanding the long-term evolution of mobile app usage
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …
Although significant effort has been made to understand mobile app usage, existing studies …
Harnessing Heterogeneous Information Networks: A systematic literature review
The integration of multiple heterogeneous data into graph models has been the subject of
extensive research in recent years. Harnessing these resulting Heterogeneous Information …
extensive research in recent years. Harnessing these resulting Heterogeneous Information …
ilocus: Incentivizing vehicle mobility to optimize sensing distribution in crowd sensing
Vehicular crowd sensing systems are designed to achieve large spatio-temporal sensing
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …
Pas: Prediction-based actuation system for city-scale ridesharing vehicular mobile crowdsensing
Vehicular mobile crowdsensing (MCS) enables many smart city applications. Ridesharing
vehicle fleets provide promising solutions to MCS due to the advantages of low cost, easy …
vehicle fleets provide promising solutions to MCS due to the advantages of low cost, easy …
Deepapp: a deep reinforcement learning framework for mobile application usage prediction
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 …
information is essential for many smartphone operations, eg, app pre-loading and content …
From Gap to Synergy: Enhancing Contextual Understanding through Human-Machine Collaboration in Personalized Systems
W Chen, C Yu, H Wang, Z Wang, L Yang… - Proceedings of the 36th …, 2023 - dl.acm.org
This paper presents LangAware, a collaborative approach for constructing personalized
context for context-aware applications. The need for personalization arises due to significant …
context for context-aware applications. The need for personalization arises due to significant …
” what apps did you use?”: Understanding the long-term evolution of mobile app usage
The prevalence of smartphones has promoted the popularity of mobile apps in recent years.
Although significant effort has been made to understand mobile app usage, existing studies …
Although significant effort has been made to understand mobile app usage, existing studies …
Enhancing mobile app bug reporting via real-time understanding of reproduction steps
One of the primary mechanisms by which developers receive feedback about in-field failures
of software from users is through bug reports. Unfortunately, the quality of manually written …
of software from users is through bug reports. Unfortunately, the quality of manually written …
Tackling higher-order relations and heterogeneity: Dynamic heterogeneous hypergraph network for spatiotemporal activity prediction
Spatiotemporal activity prediction aims to predict user activities at a particular time and
location, which is applicable in city planning, activity recommendations, and other domains …
location, which is applicable in city planning, activity recommendations, and other domains …