Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

A numerical distance based on fuzzy partitions

Authors
Serge Guillaume, Brigitte Charnomordic, Patrice Loisel
Corresponding Author
Serge Guillaume
Available Online August 2011.
DOI
https://doi.org/10.2991/eusflat.2011.99How to use a DOI?
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.
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Proceedings
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
978-90-78677-00-0
DOI
https://doi.org/10.2991/eusflat.2011.99How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Serge Guillaume
AU  - Brigitte Charnomordic
AU  - Patrice Loisel
PY  - 2011/08
DA  - 2011/08
TI  - A numerical distance based on fuzzy partitions
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1000
EP  - 1006
UR  - https://doi.org/10.2991/eusflat.2011.99
DO  - https://doi.org/10.2991/eusflat.2011.99
ID  - Guillaume2011/08
ER  -