  Understanding the structure of relationships between objects in a given
database is one of the most important problems in the field of data mining. The
structure can be defined for a set of single objects (clustering) or a set of
groups of objects (network mapping). We propose a method for discovering
relationships between individuals (single or groups) that is based on what we
call the empirical topology, a system-theoretic measure of functional
proximity. To illustrate the suitability and efficiency of the method, we apply
it to an astronomical data base.
