A numerical distance based on fuzzy partitions

DOI

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.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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 (EUSFLAT-11)
PB  - Atlantis Press
SP  - 1000
EP  - 1006
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.99
DO  - 10.2991/eusflat.2011.99
ID  - Guillaume2011/08
ER  -