Of which nature is the knowledge a similarity measure can contain? How to bring the knowledge into the measure? How to retrieve and use the knowledge for actual problems?
The semantics of similarity measures is studied and reduced to the evidence theory of Dempster and Shafer. Applications are given for classification and configuration, the latter uses utility theory in addition.