A New Algorithm of Similarity Measuring for Multi-experts’ Qualitative Knowledge Based on Outranking Relations in Case-Based Reasoning Methodology

  • Hui Li
  • Xiang-Yang Li
  • Jie Gu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)


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.


Actual Preference Similarity Algorithm Concordance Index Multiple Expert Indifference Relation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hui Li
    • 1
  • Xiang-Yang Li
    • 1
  • Jie Gu
    • 2
  1. 1.Harbin Institute of Technology, HarbinSchool of ManagementChina
  2. 2.School of SoftwareTsinghua UniversityBeijingChina

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