A knowledge base system for predicting merchandise investment returns

Charles V. Trappey, Amy J.C. Trappey, Richard Feinberg

Research output: Contribution to journalArticle

Abstract

In order to buy merchandise for resale to the consumer efficiently, the retail buyer must consider economic factors as well as the potential investment returns of the merchandise. A merchandise investment returns knowledge base, called MIR, is developed on the basis of the perceptions of an expert buyer. MIR incorporates an expert buyer's knowledge of men’s wear in regard to the relationship between economic factors, the economic outlook, and merchandise investment returns. MIR is implemented in an object-oriented, multiwindow, menu-driven environment to facilitate further system expansion. The long-term goal of the approach is to integrate the MIR knowledge base with related applications to support decision making throughout the life cycle of different classifications of merchandise.

Original languageEnglish
Pages (from-to)207-221
Number of pages15
JournalApplied Artificial Intelligence
Volume7
Issue number3
DOIs
StatePublished - 1993

Fingerprint Dive into the research topics of 'A knowledge base system for predicting merchandise investment returns'. Together they form a unique fingerprint.

  • Cite this