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

Recently, learning urban region representations utilizing multi-modal data (information
views) has become increasingly popular, for deep understanding of the distributions of …

Using multi-modal data to learn region representations has gained popularity for its ability to
reveal diverse socioeconomic features in cities. However, many studies focus solely on …

Pre-travel recommendation is developed to provide a variety of out-of-town Point-of-Interests
(POIs) for users planning to travel away from their hometowns but have not yet decided on …

The rapid advancements in sensing techniques, networking, and artificial intelligence (AI)
algorithms in recent years have brought autonomous driving vehicles closer to common use …

Semantic annotation for points of interest (POIs) is the process of annotating a POI with a
category label, which facilitates many services related to POIs, such as POI search and …

Points of interest (POIs) carry a wealth of semantic information of varying locations in cities
and thus have been widely used to enable various location-based services. To understand …

The increasing geospatial data availability has enabled extensive urban mobility studies.
However, some tasks require point-of-interest labels, which are missing or inaccurate on …