Document Type

Closed Project

Publication Date

Winter 2006

Instructor

Charles Weber

Course Title

Knowledge Management

Course Number

EMGT 510/610

Subjects

Expert systems (Computer science), Intelligent agents (Computer software), Ontology -- Applications to computer science, Knowledge management

Abstract

Ontologies, in the strict artificial intelligence sense, are used to define the allowable objects1 belonging to a universe of discourse or knowledge domain. An expert system is an artificial intelligence application that performs symbolic reasoning over a knowledge domain. When designing an expert system, the choice of a knowledge representation schema and its accompanying programmatic encapsulation largely determine the system's present and future reasoning capabilities. Therefore, for engineering and other business reasons, it is reasonable to ask if an expert system's knowledge base should be constructed from a formally specified ontology rather than by relying on implicit ontologies inherent in the chosen expert system's stereotype. This paper examines the general question of whether or not the creation of a formal domain ontology is a prerequisite to designing and building an expert system. A set of decision metrics is derived from survey data, which is then augmented by feedback from the academics and professionals who participated in the survey. The relative merits of each metric are discussed as well as topics for further investigation.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Comments

This project is only available to students, staff, and faculty of Portland State University

Persistent Identifier

http://archives.pdx.edu/ds/psu/23371

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