Task analysis interview based on task ontology

Abstract

In order to realize automated knowledge acquisition, we have to solve many problems such as lack of reusability and sharability of knowledge, which is one of the shortcomings in the current knowledge base technology, to fill the conceptual gap between the computer and domain experts and so on. Recent research activities in knowledge acquisition community are focused on task ontology, because it is expected to contribute a lot to making it easier to elicit expertise from domain experts. The authors have been involved in the research of knowledge acquisition and knowledge reuse. This article is concerned with task ontology and its use in a task analysis interview system MULTIS. We first discuss the knowledge reusability to identify appropriate task ontology. Then, we introduce a two-level mediating representation that contributes to bridging the gap and hence to making the task analysis interview fluent. MULTIS has been implemented in Macintosh Common Lisp.