Representing modeling knowledge in an intelligent decision support system |
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| Affiliation: | 1. MIS Department, School of Management, Boston University, 704 Commonwealth Ave., Boston, MA 02215 USA;2. Electrical Engineering and Computer Science, The Technological Institute, Northwestern University, Evanston, Illinois, USA;1. Instituto Tecnológico de Sonora, Cd. Obregón, Sonora 85000, Mexico;2. ITAM, Río Hondo 1, Ciudad de México 01080, Mexico;1. Institute for Integrated Energy Systems, University of Victoria, PO Box 1700 STN CSC, Victoria, BC, Canada;2. Cascadia Coast Research Ltd., Victoria, BC, Canada;1. London School of Economics & Political Science, Houghton Street, London, WC2A 2AE, UK;2. University of Oslo, Faculty of Educational Sciences, Blindern, 1161 Oslo, Norway |
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| Abstract: | Knowledge representation for data, models, and other decision support system (DSS) elements is a complex and ever-adapting task. The representation scheme for an intelligent DSS will need to provide general problem-solving model management activities as well as a mechanism for refining and testing the applicability of these models for each problem instance it encounters. We present traditional knowledge representation alternatives, and demonstrate why a multi-level scheme is superior for DSS use. We advance a two-level scheme, joining the advantages of connection graphs for the generalized analytical requirements and a frame component for problem-specific query resolution. |
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