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Aggregating Features and Matching Cases on Vague Linguistic Expressions

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Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Case-based Reasoning. Pages 252-256.

Abstract

Decision making based on the comparison of multiple criteria of two or more alternatives, is the subject of intensive research. In many decision making situations, a single criterion consists of more than one piece of information, and therefore might be regarded as a Jump of aggregated information . This paper proposes a general method for aggregating information. To accomplish information aggregation we have developed a fuzzy expert system. Results from an application of our approach in the domain of Coronary Heart Disease Risk Assessment (CHDRA) indicate the value of the information aggregation process of the system. We also show in this paper, how a case-based reasoning (CBR) system can greatly benefitin its time performance and ability to manage uncertainty-from the information aggregation method .

Alfons Schuster, Werner Dubitzky, Philippe Lopes, Kenneth Adamson, David A. Bell, John G. Hughes, and John A. White. 1997. Aggregating Features and Matching Cases on Vague Linguistic Expressions. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97. IJCAI, 252–256. https://ijcai.org/proceedings/1997/38
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