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title:
 
A numerical distance based on fuzzy partitions
publication:
 
EUSFLAT
part of series:
  Advances in Intelligent Systems Research
pages:   1000 - 1006
DOI:
  To be assigned soon (how to use a DOI)
author(s):
 
Serge Guillaume, Brigitte Charnomordic, Patrice Loisel
publication date:
 
July 2011
keywords:
 
Similarity, interpretable, expert knowledge, k-means, clustering
abstract:
 
This work studies a new distance function which takes into account expert knowledge by making use of fuzzy partitions. It considers the symbolic distances between concepts and is equivalent to the Euclidean distance for regular partitions made of triangular membership functions. Its behaviour is investigated in comparison with that of the Euclidean distance and its interest is shown for clustering applications.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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