Knowledge modeling directed by situation-specific models

Clancey (1992) proposed the model-construction framework as a way to explain the reasoning of knowledge-based systems (KBSs), based on his realization that all KBSs construct implicit or explicit situation-specific models (SSMs). An SSM is a rational argument that explains the solution produced for a specific problem situation pertaining to a target application task (e.g., SSMs constructed for typical diagnosis tasks are causal arguments having the structure of a proof). From a knowledge engineering perspective it makes sense that the notion of an SSM should play a major role in the modeling of tasks. Motivated by this view, we present a structured knowledge modeling methodology called SSM-DKM – SSM-Directed Knowledge Modeling. In SSM-DKM, an SSM is a central structure that drives the entire modeling endeavor. In light of this fact, we explain how SSM-DKM supports three main stages in the knowledge engineering process – conceptualization, formalization and validation, and instantiation – and illustrate the application of SSM-DKM to a medical diagnosis task. The knowledge model that SSM-DKM produces for a target application task has two appealing traits. First, the model embodies explicit knowledge about the ontology of SSMs that the task entails creating as solutions, thus enabling the construction of a KBS that makes these SSMs explicit. Second, the model captures strategic (or problem-solving) knowledge in declarative terms pertaining to the ontology of SSMs created for the task. Both these beneficial traits have been illustrated in the context of ACE-SSM, a KBS architecture that constructs explicit SSMs (Benaroch, 1998).