A conceptual model for optimizing the cost of knowledge acquisition

Article type: Research Article

Authors: Dos Santos, Brian L.^a | Mookerjee, Vijay S.^a | Salvendy, Gavriel^b

Affiliations: [a] Krannert Graduate School of Management, Purdue University, West Lafayette, IN 47907, USA | [b] School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA

Abstract: The most time consuming and expensive step in developing expert systems is that involving knowledge acquisition (KA). The knowledge to be acquired is generally available from many sources, for example, human experts, data bases, libraries etc. Since resources available to acquire knowledge are limited, it is important to determine how these resources should be allocated across the different sources. In this paper, this question is addressed by developing a model that determines how KA resources should be spent and how such a model may be used.

DOI: 10.3233/ISU-1991-111-203

Journal: Information Services & Use, vol. 11, no. 1-2, pp. 9-21, 1991