Meadow provided us with a summary of the issues and concerns in deciding which attributes of objects to select and the design of their values for typical information system applications. What we will be considering over the next sessions are the requirements for knowledge-based systems (sometimes labelled Expert Systems) or systems where pieces of information are related through some representation approach to allow inferences that generate actions (e.g., the execution of a sequence of instructions by a computer).

Turban, E. (1995). Decision Support and Expert Systems. New York: Macmillan. Pp. 489-498.

Skim this to provide some idea of the uses, benefits, limitations, etc. of expert/knowledge-based systems.

Taner, M., Aksoy, Y., & Arroyo, A.A. (1991). An expert system for academic counseling. Applied Artificial Intelligence, 5(3), 267-280.

This selection is offerred to ground our knowledge representation readings/discussion in a real system.

Durkin, J. (1994). Expert Systems: Design and Development. Englewood Cliffs, NJ: Prentice-Hall. [QA76.76.E95 D87 1994b] & [PAM] pp. 52-68

This selection briefly introduces the idea of knowledge and presents the idea of rule-based knowledge representation.

NOTE: You may wish to look over your notes for the Parsaye & Chignell reading from session #2 for a more in depth consideration of what knowledge is.

• Think of some information system that you have used recently. How might knowledge be incorporated into that system to enhance the system's ability to support its users' tasks? Construct a few rules that would be needed to incorporate knowledge in your system. For example, in an OPAC you might wish to followup any situation of 'no match' between a user's query and the terms employed in the database with the "firing" of such rules as: If 'college' then substitute 'university' in query.

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