Abstract
Qualitative knowledge reasoning is a key content in knowledge science. Case-based reasoning is one of the main reasoning methodologies in artificial intelligence. Outranking relation methods, called ELECTRE and others, have been developed. In this research, a new algorithm of similarity measuring for qualitative problems in the presence of multiple experts based on outranking relations in case-based reasoning was proposed. Strict preference, weak preference, and indifference relations were introduced to formulate imprecision, uncertainty, incompleteness knowledge from multi-experts. Case similarities were integrated through aggregating house on the foundation of outranking relations. Experiments indicated that the new algorithm got accordant outcome with traditional quantitative similarity mode but extended its application range.
This work is supported by the National Natural Science Foundation of China (# 70571019), the National Defense Basic Science and Research Project of China (# A2320060097), and National Center of Technology, Policy and Management, Harbin Institute of Technology.
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Li, H., Li, XY., Gu, J. (2006). A New Algorithm of Similarity Measuring for Multi-experts’ Qualitative Knowledge Based on Outranking Relations in Case-Based Reasoning Methodology. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_77
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DOI: https://doi.org/10.1007/11875581_77
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