The distance between the two elements is defined by converting the prediction confidence of the pairwise classifier, and clustering is then performed based on this distance function.
(Li et al., 2004) applied this approach to measuring name similarity in the entity identification problem, where a pairwise classifier (LMR) is trained using the SNoW learning architecture (Roth, 1998) based on variations of Perceptron and Winnow, and using a collection of relational features between a pair of names.