Smartphone app usage analysis: datasets, methods, and applications

T Li, T **a, H Wang, Z Tu, S Tarkoma… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
As smartphones have become indispensable personal devices, the number of smartphone
users has increased dramatically over the last decade. These personal devices, which are …

Mobile data science and intelligent apps: concepts, AI-based modeling and research directions

IH Sarker, MM Hoque, MK Uddin… - Mobile Networks and …, 2021 - Springer
Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of
computing with smart mobile phones that typically allows the devices to function in an …

A survey of app store analysis for software engineering

W Martin, F Sarro, Y Jia, Y Zhang… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
App Store Analysis studies information about applications obtained from app stores. App
stores provide a wealth of information derived from users that would not exist had the …

Context-aware rule learning from smartphone data: survey, challenges and future directions

IH Sarker - Journal of Big Data, 2019 - Springer
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 …

Enrico: A dataset for topic modeling of mobile UI designs

LA Leiva, A Hota, A Oulasvirta - 22nd International Conference on …, 2020 - dl.acm.org
Topic modeling of user interfaces (UIs), also known as layout design categorization,
contributes to a better understanding of the UI functionality. Starting from Rico, a large …

[HTML][HTML] Mining personal data using smartphones and wearable devices: A survey

CS Liew, TY Wah, J Shuja, B Daghighi - Sensors, 2015 - mdpi.com
The staggering growth in smartphone and wearable device use has led to a massive scale
generation of personal (user-specific) data. To explore, analyze, and extract useful …

SimApp: A framework for detecting similar mobile applications by online kernel learning

N Chen, SCH Hoi, S Li, X **ao - … conference on web search and data …, 2015 - dl.acm.org
With the popularity of smart phones and mobile devices, the number of mobile applications
(aka" apps") has been growing rapidly. Detecting semantically similar apps from a large pool …

PEVRM: probabilistic evolution based version recommendation model for mobile applications

M Maheswari, S Geetha, SS Kumar, M Karuppiah… - IEEE …, 2021 - ieeexplore.ieee.org
Traditional recommendation approaches for the mobile Apps basically depend on the Apps
related features. Now a days many users are in quench of Apps recommendation based on …

Knowledge engineering with big data

X Wu, H Chen, G Wu, J Liu, Q Zheng… - IEEE Intelligent …, 2015 - ieeexplore.ieee.org
In the era of big data, knowledge engineering faces fundamental challenges induced by
fragmented knowledge from heterogeneous, autonomous sources with complex and …

Mobile app adoption in different life stages: An empirical analysis

RM Frey, R Xu, A Ilic - Pervasive and Mobile computing, 2017 - Elsevier
The analysis of individuals' current life stages is a powerful approach for identifying und
understanding patterns of human behavior. Different stages imply different preferences and …