A proper understanding of urban functions is fundamental to prevent urban problems and
promote better built environments. While previous studies focus mainly on inferring urban …

The development of information technology has enabled many different technologies to
collect large amounts of spatial data every day. It is of very great significance to discover …

The presence or absence of some urban facilities can shape the spatial distribution of crime
occurrence. Exploring the joint influence of various types of facilities on crime occurrence …

Spatiotemporal association pattern mining can discover interesting interdependent
relationships among various types of geospatial data. However, existing mining methods for …

Co-location patterns refer to subsets of Boolean spatial features with instances of these
features frequently appear in nearby geographic space. Maximal co-location patterns are a …

Detecting regional co-location patterns on urban road networks is challenging because it is
computationally prohibitive to search all potential co-location patterns and their localities …

Spatial co-location pattern (SCP) mining aims to mine the implicit relationships between
different spatial features. These features often have certain connections and co-occur in …

Spatial co-location pattern (SCP) mining discovers subsets of spatial feature types whose
objects frequently co-locate in a geographic space. Many existing methods treat the space …

Spatial data often exhibit a tendency highly similar to spatial objects located close to each
other. Thus, prevalent co-location pattern (PCP) mining has been studied extensively to …

The detection of colocation pattern is an important and widely used method to analyze the
spatial associations of geographical objects and events. Existing studies primarily focus on …