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Knowledge level modelling: concepts and terminology

Published online by Cambridge University Press:  01 March 1998

MIKE USCHOLD
Affiliation:
Artificial Intelligence Applications Institute (AIAI), 80 South Bridge, Edinburgh EH1 1HN, Scotland. Email: [email protected] Now at Boeing Applied Research and Technology, P.O. Box 3707 M/S 7L–40, Seattle, WA, USA 98124.

Abstract

We address the problem of highly varied and inconsistent usage of terms by the knowledge technology community in the area of knowledge-level modelling. It is arguably difficult or impossible for any standard set of terms and definitions to be agreed on. However, de facto standard usage is already emerging within and across certain segments of the community. This is very difficult to see, however, especially for newcomers to the field. It is the goal of this paper to identify and reflect the most common usage of terms as currently found in the literature. To this end, we introduce and define the concept of a knowledge level model, comparing how the term is used today with Newell's original usage. We distinguish two major types of knowledge level model: ontologies and problem solving models. We describe what an ontology is, what they may be used for and how they are represented. We distinguish various kinds of ontologies and define a number of additional related concepts. We describe what is meant by a problem solving model, what they are used for, and attempt to clarify some terminological confusion that exists in the literature. We define what is meant by the term ‘problem’, and some common notions used to characterise and represent problems. We introduce and describe the ideas of tasks, problem solving methods and a variety of other important related concepts.

Type
Review Article
Copyright
© 1998 Cambridge University Press

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