Time series analysis stands as a focal point within the data mining community, serving as a
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …

Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …

Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

Accurate traffic forecasting is crucial for effective urban planning and transportation
management, enabling efficient resource allocation and enhanced travel experiences …

Mobile devices, especially smartphones, can support rich functions and have developed into
indispensable tools in daily life. With the rise of generative AI services, smartphones can …

The proliferation of geospatial data in urban and territorial environments has significantly
facilitated the development of geospatial artificial intelligence (GeoAI) across various urban …

In the geospatial domain, universal representation models are significantly less prevalent
than their extensive use in natural language processing and computer vision. This …

Urban mobility undergoes a profound decline in the aftermath of a disaster, subsequently
exhibiting a complex recovery trajectory. Effectively capturing and predicting this dynamic …

Mobility analysis is a crucial element in the research area of transportation systems.
Forecasting traffic information offers a viable solution to address the conflict between …

Urban region representation is crucial for various urban downstream tasks. However,
despite the proliferation of methods and their success, acquiring general urban region …