ACQUISITION AND VALIDATION OF COMPLEX OBJECT DATABASE SCHEMATA SUPPORTING MULTIPLE INHERITANCE

We present an intelligent tool for the acquisition of object-oriented schemata supporting multiple inheritance, which preserves taxonomy coherence and performs taxonomic inferences. Its theoretical framework is based on terminological logics, which have been developed in the area of artificial intelligence. The framework includes a rigorous formalization-of complex objects, which is able to express cyclic references on the schema and instance level; a subsumption algorithm, which computes all implied specialization relationships between types; and an algorithm to detect incoherent types, i.e., necessarily empty types. Using results from formal analyses of knowledge representation languages, we show that subsumption and incoherence detection are computationally intractable from a theoretical point of view. However, the problems appear to be feasible in almost all practical cases.