Heterogeneity in ontology-based CBR systems

This paper presents our knowledge-intensive case-based reasoning platform for diagnosis, COBRA. We work currently on the diagnosis of safety barrier failures at industrial sites. COBRA allows to author and reuse past experiences in order to diagnose new failure situations. It integrates domain knowledge along with cases in an ontological structure, which enhances its semantic reasoning capacities. We aim to make this platform as generic as possible so that it accepts different domains of application. Thus, the case structure (attributes) is defined dynamically by users at run time, which leads to a heterogeneous case base. In this paper, we present the platform architecture, the knowledge models, and the problems encountered when working with a heterogeneous case base.