Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

著者: Jörg Sander, Martin Ester, Hans-Peter Kriegel, Xiaowei Xu - Data Mining and Knowledge Discovery 1998 被引用: 1,468

The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper, we generalize this algorithm in two important directions. The generalized algorithm- called GDBSCAN- can cluster point objects as well as spatially extended objects according to both, their spatial and their non-spatial attributes. In addition, four applications using