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 …

The analysis of association rules within ecosystems is crucial for monitoring, managing, and
conserving natural resources. As widely adopted approaches for this task, geospatial …

Regional co-location pattern mining is a branch of spatial co-location pattern mining, which
is used to discover co-location patterns that prevalently co-occur in local regions. The …

The study examined fast food's geographical distribution and patronage in Calabar urban,
Nigeria. Data were acquired from both secondary and primary sources. Inferential and …

Colocation pattern mining finds a set of features whose instances frequently appear nearby
in the same geographical space. Most of the existing algorithms for colocation patterns find …

There is a Chinese proverb which states “Where there are Shaxian Snacks, there are
generally Lanzhou Ramen nearby”. This proverb reflects the characteristics of spatial …

The mining result set of spatial prevalent co-location patterns (SPCPs) is often large and
redundant, especially when the prevalence threshold is set to low or long SPCPs are …

Street space is a crucial component of public space, serving as a site for a variety of human
activities. However, prior studies have primarily focused on the traffic function of street …

Spatial co-location pattern mining (SCPM) is intended to discover subsets of spatial features
whose instances are frequently located together in geographic areas. Traditional SCPM …

大数据时代, 全面涵盖人类活动与地理环境信息的地理大数据为更全面认识“人-地”
关系提供了新的机遇. 数据挖掘是地理大数据产生“大价值” 的关键. 与传统目的性采样数据(或“小 …