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 …

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 …

Session-based recommendation (SBR) aims to recommend items based on user behaviors
in a session. For the online life service platforms, such as Meituan, both the user's location …

Personalized predictions have shown promises in various disciplines but they are
fundamentally constrained in their ability to generalize across individuals. These models are …

In recent years, predicting mobile app usage has become increasingly important for areas
like app recommendation, user behaviour analysis, and mobile resource management …

The success of online social platforms hinges on their ability to predict and understand user
behavior at scale. Here, we present data suggesting that context-aware modeling …

Living needs refer to the various needs in human's daily lives for survival and well-being,
including food, housing, entertainment, etc. At life service platforms that connect users to …

Sleep is one of the most important factors in maintaining both physical and mental health.
There are many causes of sleep problems, it is generally necessary to maintain a healthy …

Spatiotemporal activity prediction, aiming to predict user activities at a specific location and
time, is crucial for applications like urban planning and mobile advertising. Existing solutions …

Timely forecasting the urban anomaly events in advance is of great importance to the city
management and planning. However, anomaly event prediction is highly challenging due to …