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 private car aggregation effect via spatio-temporal analysis of trajectory data
Understanding the private car aggregation effect is conducive to a broad range of
applications, from intelligent transportation management to urban planning. However, this …
applications, from intelligent transportation management to urban planning. However, this …
Semantic-aware spatio-temporal app usage representation via graph convolutional network
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 …
poses a pressing need for user experience improvement. A promising solution is to model …
Modeling spatio-temporal app usage for a large user population
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 …
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
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 …
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
Forecasting crowd congestion is crucial for ensuring comfortable mobility and public safety.
Existing methods forecast crowding by capturing the increase in planned visits, which …
Existing methods forecast crowding by capturing the increase in planned visits, which …
Personalized context-aware collaborative online activity prediction
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 …
connect to online services anytime and anywhere. Naturally, user's online activity behavior …
Understanding urban dynamics via state-sharing hidden Markov model
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 …
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
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 …
risk-aware decision-making in urban regions such as congestion mitigation or crowd control …
Cityneuro: Towards location and time prediction for urban abnormal events
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 …
vital importance for emergency treatment if the location and time of abnormal events could …