Aggregating features and matching cases on vague linguistic expressions

Alfons Schuster, Werner Dubitzky, Philippe Lopes, Kenneth Adamson, David A. Bell, John G. Hughes, John A. White

Research output: Contribution to journalConference article

6 Citations (Scopus)

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 lump 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 benefit - in its time performance and ability to manage uncertainty-from the information aggregation method.

Original languageEnglish
Pages (from-to)252-257
Number of pages6
JournalIJCAI International Joint Conference on Artificial Intelligence
Volume1
Publication statusPublished - 1997
Event15th International Joint Conference on Artificial Intelligence, IJCAI 1997 - Nagoya, Aichi, Japan
Duration: 1997 Aug 231997 Aug 29

ASJC Scopus subject areas

  • Artificial Intelligence

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    Schuster, A., Dubitzky, W., Lopes, P., Adamson, K., Bell, D. A., Hughes, J. G., & White, J. A. (1997). Aggregating features and matching cases on vague linguistic expressions. IJCAI International Joint Conference on Artificial Intelligence, 1, 252-257.