ABSTRACTION OF OBJECTS BY CONCEPTUAL CLUSTERING

Very bound to the logic of first-rate predicates, the formalism of con ceptual graphs constitutes a knowledge representation language. The ab straction of systems presents several advantages. It helps to render c omplex systems more understandable, thus facilitating their analysis a nd their conception. Our approach of conceptual graphs abstraction, or conceptual clustering, is based on rectangular decomposition. It prod uces a set of clusters representing similarities between subsets of ob jects to be abstracted, organized into a hierarchy of classes: the Kno wledge Space. Some conceptual clustering methods already exist. Our ap proach is distinguishable from other approaches in as far as it allows a gain in space and time. (C) 1998 Elsevier Science Inc. All rights r eserved.