Generative model of narrative cases

Abstract

Effective case-based reasoning in complex domains requires a representation that strikes a balance between expressiveness and tractability. For cases in temporal domains, formalization of event transitions in a narrative grammar can simplify both the user's task of problem formulation and the system's indexing, matching, and adaptation tasks without compromising expressiveness. This paper sets forth a model of temporal cases based on narrative grammars, demonstrates its applicability to several different domains, distinguishes two different similarity metrics - sequence overlap and tree overlap - and shows how the choice between these metrics depends on whether nonterminals in the narrative grammar correspond to abstract domain states or merely represent constraints on event transitions. The paper shows basic-level and legal-event narrative grammars can be used together to model how human lawyers interleave fact elicitation and analysis.