Concept formation in complex domains

Abstract

Most empirical learning algorithms describe objects as a list of attribute-value pairs. A flat attribute-value representation fails, however, to capture the internal structure of real objects. Mechanisms are therefore needed to represent the different levels of detail at which an object can be seen. A common structuring method is reviewed, and new principles of evaluation are proposed. As another way of enriching the representation language, a formalism is also proposed for multi-valued attributes, allowing the representation of sets of objects.