Capacitated spatial clustering, a type of unsupervised machine learning method, is often
used to tackle problems in compressing data, classification, logistic optimization and …

Capacitated spatial clustering, a type of unsupervised machine learning method, is often
used to tackle problems in compressing, classifying, logistic optimization and infrastructure …

One of the most fundamental approaches to learn and understand from any type of data is
by organizing it into meaningful groups (or clusters) and then analyzing them, which is a …

We propose a spatial clustering method, called DBRS+, which aims to cluster spatial data in
the presence of both obstacles and facilitators. It can handle datasets with intersected …

Spatial data mining, or knowledge discovery in spatial databases, refers to the extraction
from spatial databases of implicit knowledge, of spatial relations, or of other patterns that are …

Geometrical properties and attributes are two important characteristics of a spatial object. In
previous spatial clustering studies, these two characteristics were often neglected. This …

Dealing with constraints due to obstacles is an important topic in constraint-based spatial
clustering. In this paper, we proposed the DBRS_O method to identify clusters in the …

Spatial clustering has attracted a lot of research attention due to its various applications. In
most conventional clustering problems, the similarity measurement mainly takes the …

In many geography-related problems, clustering technologies are widely required to identify
significant areas containing spatial objects, particularly, the object with non-spatial attributes …

In this paper, we propose a new spatial clustering method, called DBRS+, which aims to
cluster spatial data in the presence of both obstacles and facilitators. It can handle datasets …