Experiments in Parallel Clustering with DBSCAN

We present a new result concerning the parallelisation of DBSCAN, a Data Mining algorithm for density-based spatial clustering. The overall structure of DBSCAN has been mapped to a skeletonstructured program that performs parallel exploration of each cluster. The approach is useful to improve performance on high-dimensional data, and is general w.r.t. the spatial index structure used. We report preliminary results of the application running on a Beowulf with good efficiency.

• Type: Conference
• Year: 2001
• Where: EUROPAR
• Authors: Domenica Arlia, Massimo Coppola
• Keywords: Data Mining Algorithm, Density-based Spatial Clustering, Distributed And Parallel Computing, EUROPAR 2001, Spatial Index Structure