A survey on density-based clustering algorithms

Abstract

Density-based clustering forms the clusters of densely gathered objects separated by sparse regions. In this paper, we survey the previous and recent density-based clustering algorithms. DBSCAN [6], OPTICS [1], and DENCLUE [5, 6] are previous representative density-based clustering algorithms. Several recent algorithms such as PDBSCAN [8], CUDA-DClust [3], and GSCAN [7] have been proposed to improve the performance of DBSCAN. They make the most of multi-core CPUs and GPUs. © Springer-Verlag Berlin Heidelberg 2014.