In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
The aim of data mining is to find novel and actionable insights in data. However, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of th...
How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clu...
– Clustering is an important task in spatial data mining and spatial analysis. We propose a clustering algorithm P-DBSCAN to cluster polygons in space. PDBSCAN is based on the we...