STRUCTURING KNOWLEDGE ACQUISITION THROUGH GENERIC TASKS: A CASE STUDY IN HINDSIGHT

Abstract

Knowledge Acquisition is widely recognized as the single major bottleneck in the commercialization of Expert Systems technology. The typically ad-hoc choice of techniques for eliciting and representing expert knowledge, makes Expert Systems development expensive and prone to failure. Arguments have been made in the Knowledge Acquisition literature for performing an epistemological or "knowledge-level" analysis to "structure" the knowledge elicitation process. The need of the hour is for an empirical evaluation of these claims. In this paper, we present the results of a study that evaluates an approach to Structured Knowledge Acquisition, that is based on analyzing expert behavior using generic problem-solving tasks. Data from a large Expert Systems project currently nearing completion, has been used for the study.