A numerical distance based on fuzzy partitions

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.