Abstract
The aim of this paper has twofold: i) to explore the fundamental concepts and methods of neighborhood-based cluster analysis with its roots in statistics and decision theory, ii) to provide a compact tool for researchers. Since DBSCAN is the first method which uses the concept of neighborhood and it has many successors, we started our discussion by exploring it. Then we compared some of the successors of DBSCAN algorithm and other crisp and fuzzy methods on the basis of neighborhood strategy.