Information Sciences: an International Journal
Fuzzy Sets and Systems
Multidimensional scaling of interval-valued dissimilarity data
Pattern Recognition Letters
Clustering interval-valued proximity data using belief functions
Pattern Recognition Letters
Fuzzy skeleton by influence zones---Application to interpolation between fuzzy sets
Fuzzy Sets and Systems
Treatment of L-Fuzzy contexts with absent values
Information Sciences: an International Journal
I-Scal: Multidimensional scaling of interval dissimilarities
Computational Statistics & Data Analysis
The fuzzy approach to statistical analysis
Computational Statistics & Data Analysis
Fuzzy spatial relationships for image processing and interpretation: a review
Image and Vision Computing
On the (limited) difference between feature and geometric semantic similarity models
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
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Multidimensional scaling is a well-known technique for representing measurements of dissimilarity among objects as distances between points in a p-dimensional space. In this paper, this method is extended to the case where dissimilarities are expressed as intervals or fuzzy numbers. Each object is then no longer represented by a point but by a crisp or a fuzzy region. To determine these regions, two algorithms are proposed and illustrated using typical datasets. Experiments demonstrate the ability of the methods to represent both the structure and the vagueness of dissimilarity measurements.