In this paper we propose a novel tree-based distance function for supporting
clustering over distributed database objects. Our proposal exposes several aspects of
research innovation, which are truly established by an experimental assessment of the
accuracy of the proposed framework in computing the final clusters against both benchmark
and real-life data sets.
