OPTICS: Ordering Points To Identify the Clustering Structure

Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of the well-known clustering algorithms require input parameters which are hard to determine but have a significant influence on the clustering result. Furthermore, for many real-data sets there does not even exist a global parameter setting for which the result of the clustering algorithm describes the intrinsic clustering structure accurately. We introduce a new algorithm for the purpose of cluster analysis which does not produce a clustering of a data set explicitly; but instead creates an augmented ordering of the database representing its density-based clustering structure. This cluster-ordering contains information which is equivalent to the density-based clusterings corresponding to a b...

• Type: Conference
• Year: 1999
• Where: SIGMOD
• Authors: Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander
• Keywords: Cluster Analysis, Clustering Structure, Database, Intrinsic Clustering Structure, SIGMOD 1999