Smartphone app usage analysis: datasets, methods, and applications

T Li, T Xia, 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 …

Understanding private car aggregation effect via spatio-temporal analysis of trajectory data

Z Xiao, H Fang, H Jiang, J Bai… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Understanding the private car aggregation effect is conducive to a broad range of
applications, from intelligent transportation management to urban planning. However, this …

Semantic-aware spatio-temporal app usage representation via graph convolutional network

Y Yu, T Xia, H Wang, J Feng, Y Li - … of the ACM on Interactive, Mobile …, 2020 - dl.acm.org
Recent years have witnessed a rapid proliferation of personalized mobile Apps, which
poses a pressing need for user experience improvement. A promising solution is to model …

Modeling spatio-temporal app usage for a large user population

H Wang, Y Li, S Zeng, G Wang, P Zhang… - Proceedings of the ACM …, 2019 - dl.acm.org
With the wide adoption of mobile devices, it becomes increasingly important to understand
how users use mobile apps. Knowing when and where certain apps are used is instrumental …

Will you come back/check-in again? understanding characteristics leading to urban revisitation and re-check-in

Z Chen, H Cao, H Wang, F Xu, V Kostakos… - Proceedings of the ACM …, 2020 - dl.acm.org
Recent years have witnessed much work unraveling human mobility patterns through urban
visitation and location check-in data. Traditionally, user visitation and check-in have been …

Forecasting lifespan of crowded events with acoustic synthesis-inspired segmental long short-term memory

S Anno, K Tsubouchi, M Shimosaka - IEEE Access, 2024 - ieeexplore.ieee.org
Forecasting crowd congestion is crucial for ensuring comfortable mobility and public safety.
Existing methods forecast crowding by capturing the increase in planned visits, which …

Personalized context-aware collaborative online activity prediction

Y Fan, Z Tu, Y Li, X Chen, H Gao, L Zhang… - Proceedings of the …, 2019 - dl.acm.org
With the rapid development of Internet services and mobile devices, nowadays, users can
connect to online services anytime and anywhere. Naturally, user's online activity behavior …

Understanding urban dynamics via state-sharing hidden Markov model

T Xia, Y Yu, F Xu, F Sun, D Guo, D Jin, Y Li - The World Wide Web …, 2019 - dl.acm.org
Modeling people's activities in the urban space is a crucial socio-economic task but
extremely challenging due to the deficiency of suitable methods. To model the temporal …

Cityoutlook: Early crowd dynamics forecast towards irregular events detection with synthetically unbiased regression

S Anno, K Tsubouchi, M Shimosaka - Proceedings of the 29th …, 2021 - dl.acm.org
Early crowd dynamics forecasting, such as one week in advance, plays an important role in
risk-aware decision-making in urban regions such as congestion mitigation or crowd control …

Cityneuro: Towards location and time prediction for urban abnormal events

M Zhang, T Li, P Hui - IEEE Transactions on Knowledge and …, 2022 - ieeexplore.ieee.org
Urban abnormal events constitute a significant threat to social order and public safety. It is of
vital importance for emergency treatment if the location and time of abnormal events could …