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

Points-of-interests (POIs) have been proven to be indicative for sensing urban land use in
numerous studies. However, recent progress mainly relies on spatial co-occurrence patterns …

The past decade has witnessed the increasingly created point-of-interest (POI) data, which
are utilized to express the semantics of places. To understand the POI semantics, current …

The prevalence of location-based services has generated a deluge of check-ins, enabling
the task of human mobility understanding. Among the various types of information …

As part of invoice processing, businesses are required to manually classify each line item on
an invoice to a specific financial account. This can be time-consuming and challenging …

The categories of venues are labels, such as Museum and Bar, assigned to geographic
locations. They are often incomplete and new venues may constantly arise, making …

(1) Background: Although numerous artificial intelligence (AI)-based air pollution prediction
models have been proposed, research that links key pollution drivers, such as regional …

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 …

Point of Interest (POI) types are one of the most researched aspects of urban data.
Developing new methods capable of capturing the semantics and similarity of POI types …